SCTPLS 2001 Conference Program
Fred Abraham, Silliman
University & the Blueberry Brain Institute
This workshop will introduce some basic concepts of dynamical theory,
such as state and phase space, trajectory, vector field, attractor,
bifurcation, stability, chaos, self-organization, and some of their basic
mathematical concepts (at a very basic level), and utilizing a few classic
examples like the Lotka-Volterra and Lorenz systems plus a couple from our
fields. It will also give a brief introduction to some of the research design
and analysis issues, including attractor reconstruction, characteristic and
Liapunov exponents, recurrence plots, false nearest neighbor, and some basic
concepts of times series analysis. It will not attempt to show how to derive
theory from data; just evaluate dynamical properties of data. The morning will
be in lecture mode, and the afternoon will be a hands-on introduction to a
couple of the simpler programs around to display theory (Madonna, which is
similar to Stella) and to analyze data (Santis, beta version of Dataplore).
1700-1830
Welcome Gathering
1830- ‘til
Evening Program
featuring
Dr. Rosser is a Professor of
Economics and the Kirby L. Kramer Jr. Professor at James Madison
University. He will be discussing “The
Complexities of Complex Economic Systems”.
The application of complex nonlinear dynamics in
economics is seen as a special case of the more general multidisciplinary
development of such ideas. Arising from
bifurcation theory and more general problems of nonlinear oscillations, complex
dynamics have arguably evolved through four stages, the "four C's" of
cybernetics, catastrophe theory, chaos theory, and complexity theory. We distinguish between "broad tent
complexity" which includes all four and "narrow tent complexity"
which is the latest stage which focuses on models of dispersed, heterogeneous
agents who act upon each other locally to bring about larger scale emergent
ordered structures. Examples of
applications of all these stages in economics will be considered and their
relations to applications in other disciplines as well.
Nonlinear Paths-Not-Taken
Frederick David Abraham, Blueberry Brain
Institute, Waterbury Center
Bob Porter,
Directions
for Mental Health, Clearwater, FL rjporter@mindspring.com
Robin Robertson, General Editor, Psychological Perspectives
Science is "progressive," with each
stage in some way building on what comes
before. But sometimes science takes one path, ignoring another,
simply because it's unable yet to deal
with an issue. Sometimes, also, scientific
trajectories depend on an interaction with contextual-cultural issues.
A review of these "paths not
taken" reveals that many have non-linear dynamics at their core. The panel will present ideas from a number of thinkers, across
history, whose insights give additional flavor to current ideas in non-linear dynamics. These prescient thinkers
go back as far as the Neoplatonists -
Plotinus, Iamblicus, and Proclus - and include Bacon, Galileo, Leibniz,
Baldwin, Peirce, and James. Exploring
how these early thinkers struggled
with nonlinear concepts informs our current struggles in stimulating and productive ways. The panel
supposes this is because nonlinear
processes are at work.
The Bipolar Logistic Equation and the Concept of
Mathematical Development
Hector Sabelli, Chicago Center for Creative Development, hsabelli@rush.edu
Natural processes
spontaneously develop and decay, rather than converging to equilibrium or
chaos. Such development includes both
gradual phases and discontinuities. Recursions in which the parameter changes
in a linear or nonlinear fashion provide models for continual but discontinuous
development. The kinetic logistic
equations At+1 = At * k* t * (1 - At) and At+1 = At + At * k * t * (1 - At)
generate time series of bifurcations and chaos with prominent period 3, which
is similar to the bifurcation diagram generated by the standard logistic
equation At+1 = At * k * (1 - At) modeling scarcity. The process equation At+1 = At + k * t * sin(At) generates a
different bifurcation cascade characterized by unifurcation, sudden expansion
of chaos, prominent period 4, and bios, a nonstationary pattern containing
sensitive-to-initial-conditions bioperiodicities and infinitations [Kauffman
and Sabelli, Cybernetics and Systems, 1998].
Other recursions of bipolar feedback such as At+1 = At + At * k * t *
sin(At) and At+1 = At + (h - At) * k * t * sin(At) generate a sequence of
logistic-like developments (“logons”) Instead of blowing up, each logon
terminates with a shift to a new transient equilibrium from which a new logon
emerges, until the series converges to its attractor, either 0 or h. At appropriate initial values, the initial
logon includes a biotic phase. Logons
also appear as components of the time series generated by many other equations,
indicating that Feigenbaum cascades of bifurcation represent a natural pattern
of organization. A different road to chaos is the braid generated by recursions
of the differences between successive terms of a series At-1 - At in the
context of logistic, process or bipolar logistic recursions. These studies suggest how bipolar feedback
can generate several types of development; the observation of logistic-like
development in natural processes does not indicate their generation by
scarcity. These and other results suggest the concept of mathematical development. Mathematical developments include transient
attractors, just as natural evolutionary processes include transient
equilibrium and homeostasis.
Is schizophrenia a genetic disorder?
Perspectives from n-bind theory
Matthijs
Koopmans , MKoopmans@aol.com
N-bind theory argues that
schizophrenia is associated with contradictory patterns of interaction in the
family. The theory updates traditional family interaction models, developed in
the nineteen-fifties, using recent insights in nonlinear dynamical systems
modeling. The traditional family interaction models of schizophrenia were
discarded for lack of evidence, and because the models seemed to conflict with
the empirical findings from behavioral-genetic twin comparisons and adopted
studies. The findings from behavioral-genetic research have been used to
demonstrate a genetic basis for schizophrenia. N-bind disputes the
interpretation of these findings, and argues that family process models such as
n-bind are equally capable of explaining these results in terms of
dysfunctional patterns of family interaction, using contemporary nonlinear
dynamical systems concepts.
Information defined as energy: impact on the
process of self-organisation
Karl Toifl, University of Vienna
Karl.Toifl@akh-wien.ac.at
The traditional scientific view is to regard
matter, information and energy as basically different. Knowledge from the
theory of relativity, and especially from quantum physics, shows that at the
micro-level, matter appears to be energy if considered from the appropriate
point of view. Information has not yet been considered or discussed in this
connection, or at least not adequately. For the process of self-organization,
every complex system requires, in addition to matter, i.e. materially
compressed energy, various types of energy, as well as information of
appropriate quality and quantity. No system can function or exist without this
information. This presentation deals with information from different points of
view with respect to energy-related involvement in the process of
self-organization. Various aspects of informational energy are described, using
concrete examples, and their significance for a different interpretation of
information discussed.
Expressed emotion, emotional overinvolvement and
n-bind indicators in families with schizophrenic members
Matthijs
Koopmans , MKoopmans@aol.com
The family process models that were developed in
the nineteen fifties by Gregory Bateson and coworkers, and Theodore Lidz and
coworkers argued that the onset of schizophrenic symptoms was at least in part
attributable to dysfunctional interaction in the nuclear family. While this work had a great impact among
clinical practitioners, research failed to establish the hypothesized patterns
of interaction. An alternative model
was developed in the early to mid-nineteen-sixties, which distinguished
families who had high degrees of emotional overinvolvement (EOI) in their
interaction from those with lower levels of EOI. There is an extensive
literature indicating that if schizophrenic patients, who are hospitalized are
returned to families who interact with high levels of EOI, are more likely to
relapse than those patients who returned to families with lower EOI. In this presentation, I will look at a few
specific examples of families rated as having high levels of EOI. Based on those examples, I will argue that
in many of the typical depictions of high EOI provided in the literature, n-bind
indicators tend to occur while there are no n-bind indicators in the
descriptions of families with lower levels of EOI. This difference in clinical appearance allows us to hypothesize
that EOI, a well-established predictor of the course of schizophrenic
illnesses, may be a proxy of n-bind interactions. Conflicting attractors and
the associated turbulence in the family yields high ratings on the EOI scale,
whereas the absence of such indicators is rated as the manifestation of low
emotional EOI. If this impression is
confirmed empirically, it would appear that n-bind is an underlying mechanism
to the levels of emotional overinvolvement detected in the families of
schizophrenic patients.
On the coding of information with finite
pseudorandom sequences: Its measures and their interpretation
M.A. Jimenez-Montano, U. of
Veracruz
jimm@mail.udlap.mx
Rainer Feistel, Baltic Sea Research Institute, Warnemuende, Germany
M.A. Reigosa-Pardavila, O. Diez-Martinez, J.M. Trejo-Vargas, University of the Americas - Puebla
We consider different measures to characterize
finite objects, encoded by finite sequences under a given alphabet, called
strings. These measures, coming from information and algorithmic complexity
theories, aloud us to differentiate between strings which codify a given data
set (digitized neural-spikes, DNA and protein sequences, etc.) and sequences
generated by pseudorandom generators. Among the measures of the first kind, we
employ n-gram entropies, conditional entropies and diversity of the entropy.
Among the ones of the second kind we use context-free grammatical complexity,
algorithmic redundancy and algorithmic distance. To test different null
hypothesis, we employ surrogate sets that share selected statistical properties
with the string under study. We illustrate the usefulness of the approach with
examples taken from neuroscience and molecular biology.
Applying non-linear models to the design of
‘intelligent’ hearing aids
Ian Walker, Applied Computational Modelling Group, Department of Psychology,
U. of Bath
i.walker@bath.ac.uk
Listening to speech when it is embedded in
background noise is a particular problem for people with inner-ear hearing
impairments. Normal amplifying hearing
aids amplify the background noise as much as the speech signal, which actually
makes speech perception even more difficult because of the complicated way in
which the frequency resolution of the ear changes with the intensity of the
sounds being heard. Work is described
in which artificial neural networks are first trained with real speech signals
and then used to clean up speech that is obscured by noise. Different approaches are compared, including
a system in which the network acts as a controller, continuously altering a
series of filters to best remove background noise whilst leaving the speech
intact. It is shown that such
processing significantly improves the intelligibility of speech. These studies demonstrate how the ability of
adaptive non-linear models to extract generalities from real-world data and
then apply this learning to the solution of problems in situations of
imprecision and continual variation can be of considerable use in a real-life
situation.
Trigonometric Chaos and Bios
Hector Sabelli, Chicago Center for Creative Development, hsabelli@rush.edu
Feedback usually is bipolar (positive and
negative) in natural processes. Bipolar
feedback can generate bios, a chaotic process that diversifies in time rather
than converging to an attractor.
Heartbeat intervals series and other empirical processes show biotic
patterns [Sabelli and Kauffman, Cybernetics and Systems, 1999]. The generation of chaos and bios by bipolar
feedback is here explored by comparing a number of recursions of trigonometric
functions. The process equation At+1 = At + k * t * sin(At) generates a
bifurcation cascade (with a prominent unifurcation, a shift that looks like a
bifurcation minus a leg), 2N periods, chaos (with sudden expansion, and
prominent period 4), and bios [Kauffman and Sabelli, Cybernetics and Systems,
1998]. The recursion At+1 = At +
sin(At*(k*t)) generates a similar sequence of periodic, chaotic, and biotic
patterns although there is no increase in the feedback gain. The same patterns
obtain with the recursion of cos(At).
In contrast, recursions such as At+1 = k * t * sin(At) and At+1 = k *
t * sin(At*(k * t)) generate chaos (but
not bios) displaying two opposite sinusoidal bands. Further, the recursions
At+1 = At + k * t * cos(At) and At+1 =
At + cos(At*(k * t)) generate a logistic-like bifurcation cascade (without
unifurcation or expansion, and with a prominent period 3); the chaotic phase is organized by bands
corresponding to the cosine and its harmonics. These studies point to the
conditions required for the production of chaos and of bios. The production of
complex pattern by bipolar feedback, and the differences between sine and
cosine feedback, highlight the role of opposites in the creation of complexity.
Archetypes and Dynamics within a Unitary Reality
Bill Sulis, McMaster University
sulisw@mcmail.cis.mcmaster.ca
Robin Robertson
In "On the Nature of the Psyche", Jung commented that
"since psyche and matter are contained in one and the same world, and
moreover are in continuous contact with one another and ultimately rest on
irrepresentable, transcendental factors, it is not only possible, but fairly
probable, even, that matter and psyche are two aspects of one and the same
thing." While Jung did a great deal to explore and describe the structure
and dynamics of this unus mundus (unified world), he lacked modern non-linear
dynamic concepts. In this symposium, we will discuss some ways that archetypal
psychology and dynamics complement each other and together begin to describe
such a unitary reality.
Is Chaos Still Good for You? - Goldberger's hypothesis revisited
Dick Bird, University of Northumbria
dick.bird@unn.ac.uk
Goldberger and his co-workers have proposed, in
the context of the heart, the hypothesis that "Chaos is good for
you". Since that time this
hypothesis has been challenged, not least because of the absence of evidence
for chaos in the heart. Despite
evidence that chaos is widespread in nature doubts have also been raised about
its presence in many other biological systems.
Here the view is widened to climatological, financial, mechanical and
other kinds of system. There is a clear
overall message from many different areas which suggests that the more stable
or more adaptive systems are the ones with comparatively lower-dimensional
chaotic dynamics. While it is often
hard for a number of reasons to establish hypotheses in biological science,
this wider view makes Goldberger's original proposal seem plausible. Reasons for failure to detect chaos in some
biological systems are considered and a concept of chaostability is proposed
which might replace that of homeostasis in the regulation of biological
systems.
Simulations of an agent-based model that
consists of a large number of agents moving stochastically in a wide bounded
domain
Minoru Tabata, Kobe University
mnrtabata@wombat.or.jp
Akira Ide,
Kyushu
Tokai University, Nobuoki Eshima, Oita Medical U. Ichiro Takagi, Kyushu
Tokai U., Yasuhiro Takei, Osaka U., Michiko Yasukawa, Kyoto U.
Consider an agent-based model that consists of a
finite number of agents which stochastically move within a bounded discrete
domain to obtain higher utility. We assume that both imitative processes and
avoidance processes work in their moving, i.e., that the utility is a concave
function which attains its maximum when the density of agents is equal to a
certain positive constant. We assume that the cost incurred in moving from one
point to another point is identically equal to a positive constant or to a
linear function of the distance between the points. The agent-based model can
describe, e.g., interregional migration in quantitative sociodynamics. If the
number of agents is extremely large and the domain is very wide, then it is
almost impossible to investigate the model only by doing numerical simulations.
In order to overcome the difficulty, we employ a deterministic continuous model
to which the model converges in probability as the number of agents converge to
infinity, the size of agents 0, and the least unit of discrete space variable
0. The continuous model thus derived can more clearly describe the macroscopic
behavior of agents than the agent-based model itself. Taking a
numerical-analytic and functional-analytic approach, we deduce that the
continuous model exhibits self-organization, has an infinite number of stable
equilibria and an infinite number of unstable equilibria, and converges to a
stable equilibrium as the time variable increases.
The significance of Information for the
development of healthy or Ill states
Karl Toifl, University of Vienna
Karl.Toifl@akh-wien.ac.at
The significance of various aspects of
information, based on a clinically tested definition of “healthy” and “ill”
derived from chaos theory and self-organization, is described and discussed,
especially with regard to the creative effect it has on energy in the human
system. Health and illness are seen as qualitative states which exist at all functional
levels of the biopsychosocial entirety of the human system, and which are
subject to constant change. The state of illness is more likely when strategies
for coping with demands and problems are relatively few in number, and
relatively rigid or lacking regarding the best way of solving problems. The
state of health is much more probable when there is a great deal of variety in
the strategies available, and if they are as flexible and purposeful as
possible. The qualitative state, however, is dependent on the extent of the
demands that each system is faced with. For the emergence of such states, not
only the genetically coded information, for instance, but also a variety of
information from the psychosocial area is necessary to initiate and maintain self-organization.
Depending on the quality and quantity of the information, different qualitative
states are produced in the system. The best way to make use of this abundance
of information diagnostically is through the parallel, simultaneously integrating
use of three different, theoretically-based points of view (biologically,
depth-psychologically and systemically oriented), so as to obtain a
comprehensible diagnostic mosaic. Taking this as a basis, therapy may, for
example, include an attempt to go beyond the information already compiled, to
re-structure it or to change it along the way by adding new information, in
order that a healthier state may come about.
Diversification, equilibration, and embedding
correlation: three new statistical methods to identify creative biotic patterns
in empirical processes.
Hector Sabelli, Chicago Center for Creative Development, hsabelli@rush.edu
Minu Patel,
University
of Illinois at Chicago
Many natural processes (such as
psycho-biological and economic time series) are spontaneously creative, rather
than converging to pre-existing equilibrium, cyclic or chaotic attractors. Three new statistical methods serve to
characterize such creative processes, to demonstrate their similarity to bios
generated by bipolar feedback, and to differentiate them from chaos. In order to identify evolving processes, we
measure temporal changes in statistical parameters by measuring changes with
embedding, duration of sample, or across epochs. Diversification (temporal changes in variance) differentiate
three types of processes: (1) mechanical and random processes that maintain
their phase space volume; (2) processes that shrink to an equilibrium, cyclic
or chaotic attractor; (3) creative processes that expand their phase volume,
such as biological data, economic series, random walks, and bios. Equilibration (changes in asymmetry,
measured as skewness for normal distributions, and as the difference between
median and middle of the range for non-normal distributions) shows a
significant asymmetry that decreases with embedding for empirical series,
random walks, and mathematical bios, while chaotic and random data are
symmetric. Embedding correlation
(correlation of sets of consecutive members of a series) shows autocorrelation
(undetected by standard techniques) for the differences between consecutive
terms of biological, economic, and biotic series. Diversification, asymmetry, equilibration, and correlation
between successive changes, as well as novelty and nonrandom complexity are
characteristics that may be expected in creative processes. They are observed
in psychobiological and economic processes as well as in mathematical bios, but
not in chaotic attractors or in random series.
Applications of Difference Equations in
Mathematical Biology
Michael
Raden, Rochester Inst. Of Tech.
mradin@math.uri.edu
On the Population Model x_{n+1} = a + b x_{n-1} e^{-x_{n}} , n
= 0, 1, 2, .... where a and b are
positiove real numbers. We will investigate
the above population model and see how the long term dynamics depends on the
relationship between the two parameters a and b. We will also discuss the
extensions of the above model, previous population models, and the important
role difference equations play in mathematical biology.
Functional Differentiation in EVS models
Irina Trofimova, McMaster University
ira@ritchie.cas.mcmaster.ca
Functional Differentiation model was developed
within Ensembles with Variable Structure (EVS) approach. EVS-approach
represents interacting populations of cells with an exchange of resource and a
diversity of cells, where they seek to form connections with other cells
according to these characteristics. Model studied a role of cell's individual
thresholds of operating a resource and a role of cell's individual sociability
in functional differentiation among agents. Ratio between some types of agents
was found.
Dr. Sprott is a Physics Professor
at University of Wisconsin-Madison,author of the “Chaos Data Analyzer”
software, and an expert at visualization of complex systems. He will be discussing “Can a Monkey with a
Computer Create Art?
While
studying chaotic dynamical systems, I inadvertently generated a few million
fractal images, called strange attractors.
These images were selected by the computer from among a few billion
cases that were analyzed. I showed a
few thousand of these to about a dozen artists and scientists who evaluated
them aesthetically. From that I
discovered a strong correlation between their aesthetic quality and
mathematical properties such as fractal dimension and Lyapunov exponent. Then I was able to train the computer to be
even more selective and to produce thousands of images, all different, and most
which are aesthetically appealing. I
will describe the process and show examples of the images produced in this way
and will even produce some new ones during the talk.
Ups and downs: A dynamical systems model of
human affective fluctuations
Keith Warren, The Ohio State University
warren.193@osu.edu
Julien C. Sprott, University of Wisconsin
Studies
of subjective well being often result in counterintuitive findings. For instance, studies of subjective well being
have shown that it has little to do with life circumstance. The subjective well being of individuals
with severe disabilities is little different from those without such
disabilities (Diener & Diener, 1996), while even small events in the
immediate past can alter an individual's estimate of his or her subjective well
being (Kahneman, Diener & Schwartz, 1999).
In this paper we will link these empirical findings to a simple
mathematical model, in which individuals react to the changes in affect-ups and
downs-rather than their "objective" external state. Others, on the other hand, see our overall
state, noting such variables as our income and socio-economic status. We place this model in the form of a simple
mathematical equation, in which we see the first derivative of a function
describing our condition, while others see the function itself. While the model is related to those of
Carver and Scheier (1999) and Hsee and Abelson (1992), in which individuals
monitor their rate of progress toward a goal, we link these ideas both to
subjective well-being and to systematic differences in understanding between
observers and those observed. This
model helps to explain the remarkable resiliency of human subjective well-being
because short-term changes are likely to include both increases and decreases
regardless of one's overall external situation; thus, that situation will have
little impact on one's subjective well being.
This presentation will include empirical evidence in support of this
theory, drawn from time series analysis and from previous studies. It will also, in line with the theme of the
conference, include computer-generated graphical illustrations of the
implications of this theory.
Self-organization of landscape patterning
Janine Bolliger, U. of Wisconsin-Madison
jbolliger@facstaff.wisc.edu
Julien C. Sprott, , University of Wisconsin
David J. Mladenoff, University of Wisconsin
Self-organization is a process of evolution
where complex structures emerge from a random disordered initial state through
repeated application of simple rules.
By altering the rules and comparing the resulting patterns with those
observed in nature, it is possible to test hypotheses about environmentally
driven evolution in natural processes such as landscape pattern formation. In this paper, a stochastic, two-dimensional
cellular automaton with periodic boundary conditions was applied to a landscape
pattern from southern Wisconsin prior to Euro-American settlement, consisting
of general topological features such as prairies, savannas, open forests, and
closed forests. The cellular automaton
evolves using one simple rule: At each time step, the content of each cell is
replaced by one chosen randomly from some neighborhood of radius r. This single-parameter model gives realistic
time-varying landscapes for values near r = 5 km. The increase in organization can be measured by the statistical
distribution of cluster sizes and the fractal dimension of the patterns. These topological properties are found to be
independent of initial conditions and compare well with the same quantities
calculated for the natural landscape. The results suggest that the simple rule
suffices to explain major statistical and spatial characteristics of the
observed landscape.
Neurocognitive Synchronization
Fred Abraham--facilitator
Spatial patterns of phase in the gamma EEG
reveal episodes of fixed nonzero phase distributions recurring in the theta
range
Walter J Freeman, U of California-Berkeley, wfreeman@socrates.Berkeley.EDU
Simultaneously recorded EEGs from 64-channel
electrode arrays on visual, auditory, or somatic cortices and olfactory bulb of
rabbit brains have spatially coherent oscillations constituting a common
carrier wave. Identifiable spatial
patterns of amplitude modulation (AM) in brief segments of the coherent wave
form recur with presentations of conditioned stimuli. The 64 EEG traces seem to be synchronous, but they are not. Selected segments have a phase cone with a
gradient matching the conduction velocities of axons parallel to the pia. Modal diameter is 10 - 15 mm; modal duration
is 75 - 101 ms. Phase cones appear to
be lacking just after times of stimulus arrival but recur in pre- and
post-stimulus epochs at rates in the theta range (2-7 Hz). The spatial AM patterns reveal perceptual
constructs formed by nonlinear cortical 1st order state transitions. Because the sign of phase at the apex varies
randomly between maximal lead and lag in successive cones, we infer that the
apex of each cone marks the site of nucleation, not a pacemaker. From the phase cone we can estimate the
size, location, duration, and recurrence rate of perceptual constructs. The results support a dynamic solution to
the 'binding problem, by which the activities of 'feature detector' neurons are
integrated into percepts in the sensory cortices, in which learned amplitude
optimization compensates for nonzero phase distributions of summed signals in
the gamma range. In brief, AM patterns
give the cognitive content of the wave packets; the phase patterns show how
they form and how often.
Ultradian rhythms and control of chaos
Susan Mirow, Psychiatry Dept. U. of
Utah
SusanMirow@aol.com
Short biologic endogenous rhythms, called
ultradian, are scaling fractals, adapting to stress with changes in amplitude,
frequency and period as they entrain (couple) to each other and to the
environment. These changes are
observable on both microscopic (single cell recording) and macroscopic (sleep
rhythms, social rhythms) scales.
Entrainment of ultradian rhythms is important in attachment and
attunement behaviors as well as in the long-term effects of neglect and abuse.
These concepts are discussed as they relate to synchronization and control of
non-linear chaotic systems.
From pendulum clocks to chaos theory:
introducing control and synchronization, review and examples.
Franco Orsucci Institute for Complexity Studies, Rome
franco.orsucci@collegiumworld.org
Studying isolated and interacting systems. Brief introduction on the history of
synchronization and control studies
from Huygens to chaos theory. Review of synchronization for harmonic
oscillators to chaotic oscillators and harmonic oscillators in a noisy
environment. Typologies of coupling and synchronization in chaotic systems :
weak, strong, punctuated. Transitions
and the resulting attractors. Use of forced synchronization for control. Some
control methods: Ott-Grebogi-Yorke method, Pyragas method, Pecora-Carrol method.
Possible applications in psychology and the life sciences. Modeling
synchronization in human relations. Examples from conversation dynamics: 1)
symbolic-analogic; 2) informational.
New media, learning and synchronization
Nicoletta
Sala, Mathematics Dept., University of Italian Switzerland
nicksala@tin.it
New media (hypertexts, multimedia, hypermedia
and the Internet) are strongly
modifying teaching and learning. The aim of this presentation is to show
how it can happen. Several applications and examples on: 1) learning with
hypertexts and hypermedia (the teacher is present, synchronous communication);
2) learning with hypertexts and hypermedia (the
teacher is not present, asynchronous communication).
The Many Facets of the Holy Grail
George Williams, Federal Communications Commission
GWILLIAM@fcc.gov
We will examine a pattern that predominates in
many cultures: the sacred cup. The
predominant pattern as well as a number of variations will be explored across
many cultures, places, and times. We
will explore links that suggest a dynamic attractor in collective
consciousness.
A fractal investigation of physical factors in
human settlement behavior
Roger Sambrook, Florida Atlantic University
sambrook@walt.ccs.fau.edu
Fractal methods were used to examine the
relative importance of social and physical relief factors in settlement
behavior. The settlement patterns around a number of US cities are compared
using an estimate of clustering (mass dimension) and an estimate of ruggedness
of terrain (standard deviation of elevation). The data was analyzed to discern
if there was any correlation between clustering and ruggedness, and whether low
dimension patterns had significantly different ruggedness to high dimension
patterns. Although significant differences
in ruggedness were found between low and high dimension patterns (df=19,t=1.83,
p<0.05), only a weak negative correlation (-0.37) was found between
dimension and ruggedness. This would indicate that while settlements in flatter
areas seem to be less clustered, ruggedness of terrain cannot adequately
explain settlement patterns. This implies that social, psychological and / or
economic factors play more of a role in choosing settlement locations than do
purely physical ones.
Swarmsara: An Artificial Life Approach to
Buddhist Land Resource Management
Alex Turner, University of Wisconsin-Madison, alturner@execpc.com
Swarmsara is an artificial life simulation based
on Buddhist theory and Swarm. It
explores the interaction of emotional distortions of perception with cause and effect. Future applications might include simulation
of the emergence of cooperation and spatial land resource modeling.
Chaotic Components in Arts and Architecture
Nicoletta
Sala, Academy of Architecture of
Mendrisio, University of Italian
Switzerland
nsala@arch.unisi.ch
Chaos theory is the study of complex non linear
dynamic systems and it has a connections with the fractal geometry. Chaotic
systems have the appearance of
unpredictability but are actually determined by precise deterministic laws.
Chaotic systems show major fluctuations for apparently minor changes in the
parameters which control them. The aim
of this paper is to present some
relationships between arts, architecture, and chaos theory. In fact, it is easy to find the
golden ratio, the symmetry, the tasselations, the Fibonacci's sequence in
architecture and arts, but it is unusual
to find some relations between
the arts and the chaos. In arts many paintings have recurring shapes (e.g. spirals and vortices), that can be explained using the chaos theory,
too. For example some rock engravings
(6000 B. C.), found in a cave at
Djerat near Tassili-n Ajjer in the
South of Algeria, show some chaotic shapes. We can also
find in ancient arts (Greek art, Roman art) some S-shaped and spirals that the
science now explains using the chaos theory.
The spiral patterns symbolise activities in the life-giving boundary between order and chaos. Anthropoligists say the spiral is the
ancient symbol for the labyrinth, the twisted pathway for a journey to the core
of being. We have organised the paper
in two different parts: (a) The chaotic components in arts (e.g. the analyses of some da
Vinci's or Van Gogh paintings) , (b) The chaotic components architecture (e.g.
in the research of some strange attractors inside a plan).
Econophonia: A Sound Economic Analysis
Paul Viotti, Department of Economics, University of California at Santa Cruz
pjviotti@cats.ucsc.edu
On the cusp of a new understanding of perception
and cognition processes, this paper relates experimental economics, cognitive
psychology, and the study of complex dynamical systems. Undergraduate subjects
are tested on their ability to predict the trajectories of nonlinear
systems. The output data of nonlinear
systems are presented to the subjects, measuring their relative success in
perceiving and projecting in different sensory modalities the trajectories of
these nonlinear systems (some of which are chaotic attractors). Experimental data demonstrate the relative
efficacy of perception and projection by subjects in graphical, textual, and
"sonified" modes. I explore
applications of these findings in understanding nonlinear behavior in economic
systems.
Further up the Holler: The Fractal Nature of the
Internalized Hillbilly Stereotype
J. Howie, Pikeville College
jhowie@pc.edu
This paper approaches the relationship of
stereotype-holder to stereotyped individual as a boundary condition. Previous
research has focused on stereotypes as promoters of target group homogeneity -
but offered minimal insight into the impact of stereotyping on patterns of
self-identification within the target group. Often there is considerable
similarity between the stereotype and aspects of the target group's perceptions
of its own group members. This similarity is a function of a recursive othering
process that results from both the internalization of the stereotype and group
members' expertise at making minute intragroup status differentiations. The
nature of internalized stereotyping is such that a fractal boundary exists
between the holder of the internalized stereotype and the perceived exemplar of
that stereotype. Research on the
"Hillbilly" stereotype illustrates this phenomenon. Appalachians have
lamented and railed against this stereotype for generations - but have
internalized it so that, at the individual level, it is persistently applied to
others based on constantly refined socioeconomic and geographic distinctions. A
search for the "true Hillbilly" reveals increasingly subtle detail
used by holders of the internalized stereotype to affirm the stereotypes
"accuracy" while distancing themselves from the "proper"
target of its application. The fractal nature of internalized stereotypes
contributes to their temporal and cultural stability and partly explains their
continued persistence. This has implications for both researchers into
sociocultural phenomena and social change advocates.
The Great Depression: Computer Simulation of a
Complex Catastrophic Event
George W.
Pasdirtz, University of Wisconsin-Madison, pasdirtz@doit.wisc.edu
The Great Depression in the United States must
rank as one of the most complex and catastrophic events in the 20th century.
National Income fell by 37% from 1929-1934. Almost every sector of society
(economic, demographic and political) played some role in the event. How might
we handle the full complexity of this event while allowing a role for
cybernetics, catastrophe theory, chaos theory and complexity theory? I present results from the USGDSIM model
which is based on the Bertalanffy equation system and allows roles for complex
nonlinear dynamics, cybernetics and political "forcing functions."
The USGDSIM model decomposes early 20th Century US development into sustainable
growth paths, demographic-economic long swings and government policy
initiatives. Simulation results suggest that the 1920s boom period was the
upside of a demographic-economic cycle. The gradual return to a sustainable
growth path during the 1930s was accelerated by government policy blunders.
State space analysis of a socioemotional
transition at 18-20 months
Marc D.
Lewis, University of Toronto
mlewis@oise.utoronto.ca
Discontinuities or transitions in socioemotional
development are thought to indicate underlying reorganizations. From a DS perspective, developmental
transitions are phase transitions -- global reorganizations in the patterns of
interaction among the elements of a developing system -- and they should be
indicated by a period of fluctuation or instability sandwiched between more
stable epochs. We investigated a
socioemotional transition hypothesized to occur in the middle of the second
year (18-20 months). On 12 monthly visits from 14 to 25 months, we videotaped
infants’ behavioral adaptations to two frustrating events while their mothers
sat nearby without helping. Behaviour
was coded on two ordinal scales representing five levels of engagement with the
toy and five levels of engagement with the mother. State space grids were
constructed for each episode by plotting the second-by-second values of the two
scales on a 5x5 grid of cells. To
determine grid-to-grid stability over age, all grids were entered into a
cluster analysis. Grids with the same cluster scores were alike
topographically. An ordinal variable,
homogeneity, was defined as the degree of similarity in cluster scores across
months. Homogeneity for both tasks
showed the predicted profile, starting high, dropping in the middle months, and
then returning to a high continuous level.
Using a curve-estimation procedure, the quadratic component of the curve
(high-low-high) was significant for one task and a trend for the other, with
the estimated curve reaching its lowest point at 19 months for both. These findings indicated a period of
developmental reorganization in socioemotional functioning at the hypothesized
age.
Deviancy training as an attractor: Concurrent and predictive validity
Isabela
Granic, University of Oregon
igranic@darkwing.uoregon.edu
Thomas J. Dishion, University of Oregon
Antisocial youth engage in a process of deviancy
training in which positive affective exchanges organize reciprocal deviant talk
(e.g., talk about stealing, lying).
This pattern predicts escalations in drug use, delinquency and violence
(Dishion et al, 1995, 1996,1997). Past studies measured deviancy training by
the mean duration of rule-breaking bouts.
But a measure of central tendency does not suggest a mechanism that
links real-time processes to antisocial developmental outcomes. We have begun to conceptualize deviancy
training as an attractor which functions as an absorbing state for antisocial
peers. The current study examined a
subsample of adolescents and their best friends who were videotaped problem
solving for 30 minutes. Two groups were
compared: a nonclinical (NC) and an externalizing
group (EXT; e.g., aggressive, delinquent).
Rule-breaking and normative talk were coded continuously from the
videotapes. It was expected that over
the course of the interaction, EXT, but not NC, peers would spend increasingly
more time in a state of reciprocal rule-breaking talk. A time series representing the duration of
successive bouts of rule-breaking talk was created for each dyad, and phase
plots were derived. The plots showed
that bout duration increased over time for EXT but not NC youth. To quantify these impressions and examine
their predictive validity, slope values were derived from the time series and
entered into two logistic regressions to predict concurrent and future clinical
status. As hypothesized, for the
analysis of the concurrent measures, slope values significantly differentiated
the EXT and NC group, with the EXT group showing a positive and the NC a
negative slope profile. More
importantly, the slope profiles significantly predicted clinical group status
two years later.
Depiction of Dynamic Patterns in Self-Organized
Group Formation using Vector Fields and Phase Portraits
Holly Arrow
harrow@darkwing.uoregon.edu
When formerly unacquainted people self- organize
into groups, they create new structure at the group level and at the level of
the larger social network that contains both emergent groups and isolates.
Dynamic patterns of continuity and change at these two levels were examined for
30 sets of 8 people who repeatedly formed groups as part of a social card
game. Network analysis measures of change
over time, such as the QAP correlation, indicated that some of the miniature
"societies" settled into a stable set of groups and isolates, but
most did not. At the society level, the
dynamics indicated an increasing trend away from isolates and toward full
inclusion of all members in groups. Transition probabilities were used to
construct vector fields that illustrate how the patterns of group size differ
when these developing "societies" were perturbed either early in the
process of self-organization or later on.
Phase portraits illustrate qualitative differences in trajectories for
different societies. The perturbation was a change in the payoff structure for
the game. Contrary to expectations,
changes in societal configuration were not coordinated with external
perturbations, although changes in group composition were. Questionnaire data
revealed that endogenous change in the social organization occurred when
individual dissatisfaction was communicated and reinforced at the dyad or group
level.
Using State Space Grids to Depict Phase Transitions
in Adolescent Development
Tom Hollenstein, University of Oregon
tomh@oslc.org
A basic tenet of developmental stage theories
has been that development is characterized by a number of discontinuous, abrupt
shifts. The current paper reports on a study designed to examine the structural
differences in adolescent boys’ behavior before, during and after one of these
critical periods, puberty. We hypothesized these changes would exhibit the
characteristics of a phase transition - behavior both before and after puberty
would be relatively stable but, during the transition period, behavior would
become less stable and more variable. We tested this hypothesis on 61 boys and
their mothers participating in the Oregon Youth Study using real-time
observations of their problem-solving discussions videotaped once every other
year between the ages of 10 and 18. We created state space grids for each dyad
at each wave. These grids are plots of behavior in real time with each subject
on separate axes such that a point represents a dyadic turn and, when the
dyad’s behavior changes, a new point is plotted and line connects them. Using
the number of unique cells in the state space visited per unit time as our
dependent measure, we found a significant quadratic trend, maximum variability
during puberty (age 13-14). Implications of these results for both normative
and non-normative development are discussed.
A New Approach to Nonlinear Decision Function of
Social Process: Professor Helbing's Decision Theoretical Specification
Y. Aruka, Faculty of Economics, Chuo University, Tokyo
aruka@tamacc.chuo-u.ac.jp
The idea of utility function by itself is too
poor to contribute into social decision theory. Social decision function and
welfare function of traditional economics should be replaced with a new
analytical form. Social interaction of agents is a process of mutual influence
for better or worse. Utility of each agent is always affected not only by
others' behavior but also by subgroups’ characteristics to which each belongs.
Decisions in many cases evolve as a result of nonlinear aggregate dynamics,
which can be expressed in terms of master equation, as long as the variables in
a system are a few. The key issue to achieve this hinges on the definition of the
transition rate." Social dynamics of Weidlich and Haag(1983), in other
words, social synergetics is a pioneering work in this sense. Recently,
Helbing(1995, pp.132-137) skillfully in this context was successful to define
an analytical form of decision of social interaction. Helbing has an insight
that utility has a past history of decision sequence and also cannot be
independent from it. His utility function should rather be called a
psychologically complex value. Consequently, utility will fluctuate like in
human mind. He specified the elements like flexibility, distance and effort,
attractiveness for decision by a subgroup to define readiness of decision. Thus
the social transition rate for a subgroup could be foumulated. Such a social
transition rate will be operated in the master equation of social process.
Incidentally, this transition rate may be applicable to the Avatamsaka game
process given by Aruka(2000) and Aruka(ed.)(2001).
Multiple Unofficial Economy Equilibria and Income
Distribution Dynamics in Transition Economies
J. Barkley
Rosser,
Jr., James Madison U.,
rosserjb@jmu.edu
Marina V. Rosser, Economics
Ehsan Ahmed, Economics
Large increases in the relative size of
unofficial economies in many transition economies arise from a dynamic
interaction with rising income inequality and public sector changes in multiple
equilibria systems. Returns to unofficial activity are first increasing and
then decreasing, implying two distinct stable equilibria, with changes in
inequality possibly causing a jump from one to the other quite suddenly. Multiple regressions of data from 17
transition economies find income inequality strongly associated with the
relative size of the unofficial economy and also increases in income inequality
with increases in the relative size of the unoffical economy. Other significant variables positively
associated with the unofficial economy include the maximum annual rate of
inflation, the effective marginal rate of capital taxation, and an index of
economic freedom.
Avatamsaka Game Experiment as a Nonlinear Polya
Urn Process
Y. Aruka, Chuo University, Tokyo
aruka@tamacc.chuo-u.ac.jp
Avatamsaka Game appearing in Aruka (2000) and
Aruka (ed.) (2001) which describe a social dilemma appearing when we assign
such a pay-off structure that (defect, defect) = (0, 0), (cooperation, defect)
= (0, 1), (defect, cooperation) = (1, 0), (cooperation, cooperation) = (1, 1).
The interesting feature of this game appears in that cooperative players cannot
necessarily be guaranteed their own gains by their behavior. This game
experiment has been undertaken in Tokyo, Milwaukee, and Frankfurt am Main. The
results of successive experiments on the web specifically in cooperation with
Stephen J. Gaustello at present are giving some new insights on human behavior.
In order to analyze these, we need a theoretical hypothesis of path dependency
on each player’s strategy policy. In order to do this, the author suggests the
use of nonlinear Polya urn process, which was rediscovered by Arthur(1994) , a
Santa Fe economist, as a main force of path dependency.
Let It Be; Chaotic Price Dynamics can be
Beneficial
Akio Matsumoto, Chuo University
akiom@tamacc.chuo-u.ac.jp
The main purpose of this study is to address the
question of whether consumers can benefit chaotic price instability. This
question was raised by Wough [1944, Quarterly Journal of Economics 58, 602-614]
more than a half decade ago, and a positive answer was given only under a very
limited circumstance. The same question is reconsidered in this study with a
help of the recently-developing
nonlinear dynamic theory. To this end, we study price adjustment in a
disequilibrium model in which trade occurs at disequilibrium prices. To make such
an analysis possible, we formulate a consistent adjustment model that takes
disequilibrium phenomena into account and organize the study as follows: (1) we
outline a basic pure exchange economy and then show to constitute the logistic
map as a dynamic system of the model; (2) we analytically demonstrate that the
long-run average utilities taken on chaotic paths can be preferred to a
stationary utility (i.e., a utility taken at a stationary state) under specific
parameters' values; (4) to confirm and complement the theoretical result, we
perform some numerical simulations that give rise to the same results. The main
result of this study, namely, chaotic price dynamics can be beneficial to
consumers, will shed light on the nature of long-run irregular dynamics that
has been neglected in the traditional economics.
Control of Hyperchaos in an OLG Economic Model
Vivaldo
Mendes,
ISCTE, U. of Lisbon
vivaldo.mendes@iscte.pt
Diana A. Mendes
This paper deals with the control of chaotic
economic motion. We show that very complicated dynamics arising, i.e., from an
overlapping generations model (OLG) with production and an endogenous
intertemporal decision between labour and leisure, which produces hyperchaos
(both eigenvalues with values higher than unity), can in fact be controlled
with relative simplicity. The aperiodic and very complicated motion that stems
from this model can be subject to control by small perturbations in its
parameters and turned into a stable steady state or into a regular cycle. We
apply the pole-placement technique, developed by Romeiras, Grebogi, Ott and
Dayawansa (1992), to control the chaotic dynamics of this economic model. The application of control methods to
chaotic economic dynamics may raise serious reservations, at least on
mathematical and logical grounds, to some recent views on economics which have
argued that economic policy becomes useless in the presence of chaotic motion
(and thus, that the performance of the economic system cannot be improved by public
intervention, i.e., that the amplitude of cycles can not be controled or
reduced). In fact, the fine tuning of the system, or its control through an
external force, can be performed without having to rely only on infinitesimal
accuracy in the perturbation to the economic system, as the control can be
performed within a relatively large (but not too large) subset of the
linearized parameter space.
SAT 1800- ‘til
Social Hour and Banquet featuring
STEPHEN GUASTELLO
Dr. Guastello is one of the earliest
members of the Society, Editor of our journal Nonlinear Dynamics, Psychology,
& Life Sciences,and a leading expert on catastrophe theory. He will be discussing “20 years of Nonlinear
Dynamics in Organizations”
The year 2001 marks the 20th
anniversary of the first journal article where principles of nonlinear dynamics
were applied to phenomena in organizational psychology. This presentation
highlights the landmarks in theories of organizational development, work
motivation and personnel selection, creativity, coordination in work teams,
leadership emergence, work performance in hierarchies, and strategic
management. The accuracy associated with empirical results supporting nonlinear
theories is approximately double the accuracy associated with linear theories.
Together we will explore the ever-growing frontiers of nonlinear dynamics
applications.
Multilevel Webs As Non-Deterministic Complex
Systems
Christine
Hardy, Centre Eco-Mind
101515.2411@compuserve.com
As soon as we reach a certain threshold of
complexity, in synergetic systems, events and outcomes are no more following a
deterministic course, even nonlinear deterministic bifurcations. Multilevel
webs are systems that 1) exhibit internal multiplicity in organizational
levels, and 2) show cooperative interactions and inter-influences between
connected networks/processes, within and across levels, so complex that they
render determinism irrelevant as a formalism. An example of such multilevel
web, in which various forces or subsystems interact simultaneously within and
across levels, is the human mind: in the mind-body-psyche system (MBP-system),
sensations interact and co-evolve with thoughts and feelings, and all these
processes are themselves linked to neuronal networks. If local deterministic dynamics may be extracted (e.g. drinking
alcohol will induce such and such somatic and neuronal changes),
non-deterministic inter-influences are the most pervasive dynamics in the
MBP-system. For example, an individual may use the drunk state in a variety of
ways, e.g. to be artistically creative, and their subsequent creation will be
undetermined. Mind dynamics such as
intention, will, creativity, innovation, feelings, artistic sense, sense of
humor, sense of beauty, and peak experiences, are fundamentally
non-deterministic. They are web dynamics that imply creative emergence, based
on complex inter-influences between multiple levels in the MBP-system, as well
as inter-influences between these and surrounding webs¾such as other people,
organizations, society at large, and environmental webs. Thus cognitive
multilevel webs demonstrate creative self-organization and free-will.
Mapping the Unpredictable: the Dynamical Nature of Mood and Emotion
Susan Mirow. Dept. of Psychiatry, University of Utah School of Medicine
Susan.Mirow@aol.com
The non-linear, dynamical nature of mood and
emotion is explored, first
phylogenetically and then as it appears in healthy and pathological states, under conditions of both normal and abnormal
stress. A scale-invariant (fractal)
measure of mood and emotional state appears to be the biological rhythm known
as ultradian. Ultradian rhythms are endogenous biological oscillations shorter
than 24 hours in duration. Examples of
this fractal measure may provide information as to the unfolding of the stress
response syndrome, Posttraumatic Stress Disorder. Posttraumatic Stress Disorder
has been characterized by catastrophic alterations in mood and emotional state
that appear to be triggered by small environmental cues. Other human conditions such as aging, or
persistent pathological states such as those found in Bipolar Disorder or
Alzheimer's Disease may be understood as dysregulations of ultradian rhythms to
the circadian cycle. These conditions show a loss of complexity of integrated
function that is measurable using non-linear tools. We know that pathological
environments can change the brain in enduring ways, constricting both the range
and intensity of emotional expression. Successful treatment of psychiatric
illness, by whatever method, returns emotional responsiveness to physiological
norms. Healthy states of mood and emotion provide maximum flexibility in
adaptation to changing conditions, while the aging brain is restricted to
unmodulated and inflexible responses to new conditions, thereby limiting
adaptation. The evolution in
complexity of brain organization is responsible
for the emergent system of mood and emotion. Ultradian rhythms, as fractal
measures of mood and emotional state may prove useful in both diagnosis and
treatment of psychiatric conditions.
Modeling High-Resolution Broadband Discourse in
Complex Adaptive Systems
Kevin Dooley, Arizona State University
kevin.dooley@asu.edu
Steve Corman, Arizona State University
Robert McPhee, Arizona State University
Tim Kuhn,
U.
of Colorado
Numerous researchers and practitioners have
turned to complexity science in order to better understand human systems. Simulation is commonly used to observe how
the micro-level actions of many human agents create emergent structures and
novel behavior in complex adaptive systems.
In such simulations, communication between human agents is often modeled
simply as message passing, where a message or text may transfer data, trigger
action or inform context. Human
communication involves more than the transmission of texts and messages,
however. Such a perspective is likely to limit the effectiveness and insight
that we can gain from simulations, and complexity science itself. In this paper we propose a model of how
close analysis of discursive processes between individuals (high-resolution),
that occur simultaneously across a human system (broadband), dynamically
evolve. We propose six different
processes that describe how evolutionary variation can occur in
texts—recontextualization, pruning, chunking, merging, appropriation, and
mutation. These process models can
facilitate the simulation of high-resolution, broadband discourse processes,
and can also aid in the analysis of data from such processes. Examples are used to illustrate each
process. We make the tentative
suggestion that discourse may evolve to the “edge of chaos”. We conclude with a discussion concerning how
high-resolution, broadband discourse data could actually be collected.
Chaos Theory, Visualization And Psychogical
Change
Rita Weinberg, Professor of Psychology, National-Louis University
rweinberg@nl.edu
This paper describes the relation of
visualization to psychological and behavioral change. As a function of brain processing, the power of visualization,
when understood and utilized can be formidable in healing and making positive
changes in attitude, perspective and re-organizing internal states. The majority of people in our country use
visualization as their preferred representational system.. That means that our
brain uses visualization as the first filter in processing incoming information. Chaos theory postulates that depending on
initial conditions, a small change can lead to very large changes. With visualization, small shifts, when
appropriately applied, can lead to major and compelling changes in behavior and
attitude. Tiny shifts may appear to be
fractal, but they are not. Those slight modifications are indexes of a very
different picture and are critical to the change process. Since our brain stores past experiences in
memory, visualization can change our feelings about past experiences. Similarly it has the power to propel us into
a compelling future, with appropriate visual shifts.. Minor adjustments can change a negative visualization into a
positive one. Negative pictures often
stimulate anticipatory anxiety or phobia behavior. Chaos theory leads to our understanding of many elements about
how visualization works. We still do
not understand why it should be such a powerful force for processing
information in our brain.
Human communication as complex system: a
quantitative analysis
Giovanna
Morgavi, I.C.E., National Research Council, morgavi@ice.ge.cnr.it
Fabrizio Manca, University of Turin
Over 1000 research interviews made from students during their psychology university
course have been analyzed. Our goal was to extract information on the evolution of a communicative process through
simple quantitative measurements and with a particular attention to avoid any
simplification form or classification.
As in medicine blood analysis parameters can give an indication on the health state of a patient, our goal was
to extract some measured indication on the “state” (correctness) of these psychological interviews. The whole
interview process has been considered as a complex system evolving in the time. The nature intrinsically interactive
of the dialogue concretizes, shapes and evolves within time dimension. A
reciprocal adaptation, where each partner learns, step by step, to lead in the
interlocutor’s reference frame, without quitting its own, turns into a common system exceeding those of both
fellow. During the interaction, the turn alternation is fundamental, specially
when the mutual definition of the relationship involves the acknowledgement of
different roles. Through word counting
we estimated the conversation
process time series from which we plotted the“ phase-portrait”. Some parameters
defined as function of the phase portrait space occupancy give very good indication on the process
evolution and on the observance of the psychological interview laws. This
procedure allowed information extraction on the conversation evolution without
any semantic analysis: plots with anomalous paths indicate situations where the
communication has been troubled.
Ordering, intelligence and entropy
Marc Defourneaux, MarcDfnx@aol.com
In a gas, sorting out randomly moving molecules
so as to deliberately redirect their courses would imply the intervention of an
intelligent actor: Maxwell's "demon". Similarly, at a macroscopic
level, retrieving randomly scattered elements (e.g. cardboard squares with a
letter written on one side) and placing them in perfect order (namely on an
alphabet) is a common way of developing a child's intelligence: the less
groping the better, as opposed to a dumb machine which would try each possible
position for each element until they match.
However, even the intelligent player scans the model with his/her eyes
before finding the right position for each element. All the worse if the
alphabet is not in the normal order, as memorized for years in the player's
brain. More generally, human performance results from two factors: actual
"intelligence" based on understanding the logic of the model, and
apparent "intelligence" which only consists in replacing mechanical
groping with visual groping or scanning one's memory. Therefore, intelligence reduces the cost for decreasing entropy
but does not zero it: in a partly assembled jigsaw puzzle, transferring a piece
from the "chaos" to the already ordered subset requires several
trials, whereas the opposite transfer only requires one move. This
irreversibility suggests a thermodynamic analogy by considering the number of
trials in the ordering process as the energy, be it mental required to decrease
the entropy and "cool" the system. This "cooling" is
obviously fictitious, but this analogy bridges a gap between statistical
physics and the intelligence theory.
Coupling dynamics of motion primitives in speech
movements and its potential relevance for fluency
P.H.H.M.
van Lieshout, University of Toronto
p.vanlieshout@utoronto.ca
This paper discusses a, for speech research,
novel approach in which speech movements are treated as a complex sum of
individual motions (primitives), generated by a self-organizing system of
coupled neural oscillators. In this approach, the individual primitives are
studied separately for their coupling dynamics as expressed in continuous
estimates of relative phase. Using kinematic data from normal speakers and
people who stutter under various task conditions, destabilizing influences to
the coupling of dominant and non-dominant primitives are discussed with respect
to their potential relevance to explain perturbing effects on speech fluency.
Visualizing and Quantifying Nonlinear Dynamics
in Human Cognition
Richard Heath, University of
Sunderland, UK
richard.heath@sunderland.ac.uk
Alice Kelly
& Andrew
Heathcote, University of Newcastle,
NSW, Australia
Human cognitive processes evolve over time and
so offer a challenging medium for understanding complex dynamical systems. We
examine how nonlinear visualisation and quantification technologies, originally
devised by physicists, can be effectively employed to understand cognitive
processes. These techniques include the use of third moment asymmetry to
determine the presence of nonlinearity, the separation of stochastic and
deterministic processes using noise-reduction methods; and the important issue
of detecting nonstationarity using parametric and nonparametric techniques.
These methods are illustrated using human response time data in n-choice
tasks. Problems associated with
psychological measurement and some possible solutions are highlighted.
Memory across Eye-Movements: 1/f Dynamic in
Visual Search
Deborah J.
Aks, University of Wisconsin—Whitewater, aksd@mail.uww.edu
Gregory Zelinsky, Department of Psychology, State University of New York
Julien C. Sprott, University of Wisconsin
The
presence of apparently random behavior in visual search (e.g., Horowitz &
Wolfe, 1998) has led to our proposal that the human oculomotor system may have
subtle deterministic properties that underlie its complex behavior. We report
the results of one subject’s performance in a challenging search task in which
10,215 fixations were accumulated. A
number of statistical and spectral tests revealed both fractal and 1/f
structure. First, scaling properties emerged in differences across eye
positions and their relative dispersion (SD/M), both decreasing over time.
Fractal microstructure also emerged in an Iterated Function Systems test and
delay plot. Power spectra obtained from the Fourier analysis of fixations
produced brown (1/f2) noise and the spectra of differences across eye positions
showed 1/f (pink) noise. While the sequence of absolute eye positions resembles
a random walk, the differences in fixations reflect a longer-term dynamic of
1/f pink noise. These results suggest that memory across eye-movements may
serve to facilitate our ability to select out useful information from the
environment. The 1/f patterns in
relative eye positions together with models of complex systems (e.g., Bak, Tang
& Wiesenfeld, 1987) suggest that our oculomotor system may produce a
complex and self-organizing search pattern providing maximum coverage with
minimal effort.
Multilevel model of creative thinking and the
principles of CA simulation
N. Aniskovich, European Humanities University, naniskovich@mail.ru
We propose the multilevel model of creative
thinking which is based on a dynamical systems approach to cognitive systems.
The levels are the semantical level (or sense transformation level) or the
level of logics and grammar (in proposed model they are unified). Dynamical
patterns are used as substitutions for representations in cognitive theories.
The dynamics of each level, which is supposed to be chaotic, allows for the
generation of new information not presented by initial conditions. In creative
thinking consideration we use the results of some tests where the task of story
generation from the schedule of some words is used. The normal strategy is
considered when at first some general ideas relevant to story are generated and
only then verbalization takes place. We suppose that two-levels model can be
applied for cognitive simulation with CA as an example. Class 3 and 4 CA are
considered as having properties essential for hierarchical systems
functioning.
Modeling dynamics of operant behavior controlled
by fixed-interval (FI) schedules
Jay-Shake
Li, IUniversity of Düsseldorf, Germany, lijay@uni-duesseldorf.de
Joseph Huston, University of Düsseldorf
Considerable effort has been invested to model
the functional mechanisms of operant behavior.
Most of the this work has been devoted to the measurement of changes in
behavior as a function of parameters defined in the reinforcement schedules,
which usually predict averaged values of behavior across several sessions. Thus they were far from being equations of
motion in the sense of Newton’s classical dynamics, which dealt with real time
behavior of systems. One possible
reason for the rarity of studies in this direction might be the poor capability
to analyze highly irregular time series data, the inter-response-time (IRT),
from a typical operant experiment.
Since the introduction of the Extended Return Map (ERM) last year, we
have a better analyzing tool to extract information out of these complex data
sets. In the present work, we built two
models to simulate the IRT data from a Skinner-box experiment using
fixed-interval (FI) reinforcement schedules.
Both models reproduced frequency distributing curves of IRTs similar to
the experimental data. They could also
correctly reproduce the stereotypical scalloped curve shown in cumulative
records of Skinner-box experiments controlled by FI schedules. However, they differed in their formulation
in one important feature: While one model used a continuous function to describe
the occurring probability of operant response, the other one employed an abrupt
switch from one behavioral state to another.
Comparing the ERM of both models with the experimental data revealed
that the abrupt switch of behavioral states was an essential part in the
functional mechanism of operant behavior under FI schedules.
The Self as Coagulated Interaction
Guido Hucke, aron2@freenet.de
According to Duerr - successor of Heisenberg at
Munich - the whole universe can be seen as one system which only consists of
interaction. Sometimes this interaction coagulates into solid forms which we
then call matter = substance. But at first the universe has to be understood as
an ever changing process. Iwill use this metaphor for describing and defining
the Self. In my (and others) opinion the Self only consists of interaction,
coagulated interaction. From outside the Self seems to be something solid, and
indeed our Selves are psychologically impenetrable to each other, like our
bodies are physically impenetrable. From inside the Self seems to consist of
all possible relationships to all possible material and mental
"worlds". Using this metaphor every form of (human) communication =
interaction can be understood as BEING an all comprehensive general field. Because
in this point of view we ARE interaction = communication = conversation, we
consist of inner and outer dialogues (see Gadamer and Luhmann). Finally, some
problems with self-reflection or self-iteration will be discussed.
The Chaos of Health
Mario E.
Martinez, Institute of Biocognitive Psychology, Nashville, Tennessee
IBP@biocognitive.com
This paper presents a model of health and
illness based on the author’s theory of Biocognition. It argues that health is
a bioinformational process that constantly oscillates between chaos-like
non-linearity and linearity. When this oscillation collapses into a repetitive
linear loop, it loses coherence with its bioinformational field creating a
rigid state of pathology. Based on the
last thirty years of research in the interdisciplinary field of
psychoneuroimmunology and in medical anthropology, Biocognitive theory suggests
that the individual is an inseparable unit of cognition, biology and historical
culture. This paper also argues that health and illness are neither exclusively
biological nor totally mental. All human processes are inseparable
biocognitions of mindbodyculture.The bioinformational field is contained by
horizons functioning as attractors that oscillate from stability to instability
in the process of communicating and learning. This oscillation is considered to
be operational at all levels of the bioinformational field ranging from the
cognitive to the cellular modes of
communication. Biocognitive
theory considers the reductionist and dualist limitations of upward and
downward causality and offers an alternative the author calls contextual
coemergence. This model of coemergence suggests that causality is a co-authored
and simultaneous process that takes place within and between bioinformational
field horizons rather than originating at either the molecular (reductionism)
or cognitive (expansionism) levels of life.
Contextual coemergence includes non-linear phases where Chaos theory can
offer heuristic as well as practical advantages over the linear models of
conventional life sciences.
Information & Interface
Arnold J.
Wytenburg, Change Adoption Practices,
arnold@originalthinking.com
Western culture is based on the notion of
information as quanta, as discreet things that ‘stay still.’ At least since the
birth of mathematics, this notion has shaped our ideas about media and their
role in simultaneously constraining and making our enterprises possible. But
information isn’t what it used to be. Today’s sociotechnical substrate is
electronic information is now ubiquitous and ethereal. The landscape of this
‘information space’ is in continuous flux; boundaries are dynamic, uncertain
and ambiguous. Information is now simultaneous, continuous, tentative ‘Brownian
motion’ that is affective outside of the old notions of time, space and
function. In this regime, the coherence of the network of ideas that act to
simultaneously describe and shape our reality must dominate the cultural
agenda: relationship counts more than position. Rich relationships are
subjective unstable and cannot be readily negotiated outside of ‘the moment.’
Emphasis on insisting sameness to stay the vertigo of an overwhelming diversity
of moments in flux is running its course. The nature of socioelectronic reality
is highly dimensional. A culture’s meaningful participation in that context
requires apprehending information as fluid, the socioelectronic environment as
interface, and that interface as a ‘space of possibilities.’
Picture Yourself: Exploring the Dynamics of
Vision and Posture
Mark R.
Filippi, addchiro@mindspring.com
The integrity of the relationship between vision
and posture determines the conversational tone of the nervous system. It has been estimated that 90% of the
brain’s sensory input comes from visual sources. Even 20% of posture is associated with vision. The most powerful influences on learning
potential are concrete, vivid images. Enhanced clarity, creativity and insight
have been associated with a posturally modulated phenomenon called cortical
facilitation. The confluence of other related systems, ranging from vagal and
frontolimbic activity to the architecture of the retina itself, help us
distinguish memory from experience.
After a review of related clinical concepts, a series of interactive
group exercises will be used to illustrate these axioms.
Characterizing and Exploring the
Government/Industry Cluster Time-Ecology
Gus Koehler, ED>Net, koehleg@ednet.cc.ca.us
There are numerous studies of policy making, on
the design, implementation and evaluation of economic development programs, on
the life-cycles of government organizations and of businesses, on business
networks, and on how regional economies are organized and work. But, there is little understanding of how
all of these elements work together.
That is, how multiple public economic development programs combine and
interact on a single firm, with a large number of individual businesses, or on
business networks in regional economies to produce competitive advantage. There
is even less understanding of how these systems and processes grow, coevolve,
and change over time. This paper will
present on-going work that uses the concept of a time-ecology to investigate
some of these relationships. Particular
attention will be paid to how the heterochornic interactions of agent time,
clock time, and nootemporal time that form public policy making and government
agency activities.
Simulating people’s cognitive responses to
health threats
Sarah Milne, University of Bath
s.e.milne@bath.ac.uk
Ian Walker,
University
of Bath
Rob Lowe,
University
of Wales Swansea
Psychologists aim to model decision making and
behaviour. Traditionally, such models assume linearity and rationality. Two
studies are presented looking at the ability of non-linear models to predict
decision making in response to different health threats. In Study 1, 219 men
read an educational leaflet about testicular cancer and self-examination, then
completed a questionnaire measuring their appraisals of the threat of cancer
and their ability to cope with it. A
neural network learnt to associate these variables with adaptive and
maladaptive coping responses from half the participants. This accounted for 67% of the variance in
the untrained participants’ coping measures (multiple regression, by contrast,
predicted 38%). Moreover, the dominant
linear model in this field identifies only one way in which each coping response
can be produced. In contrast, this
data-driven analysis identified new decision-making profiles when the model’s
internal representations were cluster analysed. For example, two groups of people with high behavior-change
intentions were found, each of which formed this intention through very
different cognitive processes. This
clearly shows a more complex decision-making process than has been previously
recognized. Study 2 used similar
techniques to explore the role of personality and individual differences in
predicting intention to perform stress-reduction techniques, as well as
comparing this approach with that of an adaptive neural fuzzy logical
model. These studies demonstrate that
non-linear techniques are of particular value where a behavioral/personality
variable must be predicted from a complex array of other measures. Theoretical
and practical implications will be discussed.
Effects of Verbalization and Personnel
Replacement on Group Coordination, and Leadership Emergence in
Coordination-Intensive Tasks
Stephen
Guastello, Marquette University
stephen.guastello@marquette.edu
Benjamin R. Bock, Philip Caldwell,
Robert W. Bond, Jr., Marquette University
Coordination occurs when two or more people do
the same or complimentary tasks simultaneously; its explanation game theory,
nonlinear dynamics, and implicit learning theory. The objective of the study
was the to assess the impact of the replacement of group members, verbal versus
nonverbal communication, and leadership emergence on the dynamics of
coordination acquisition and transfer. The general dynamic was one of
self-organization if learning was complete enough, and chaos where
self-organization was not complete (Guastello & Guastello, 1998).
Leadership was hypothesized to emerge according to the swallowtail catastrophe
function that was identified in previous studies (Guastello, 1998; Zaror &
Guastello, 2000). In the first of two experiments,12 4-person groups were
allowed to discuss the coordination (card game) task while performing it; 12
other groups worked nonverbally. Varying numbers of group members were replaced
during the game. Split-plot ANOVA
showed that verbalizing groups performed better than nonverbalizing groups
overall and showed more acute coordination learning curves, but verbalization
did not compensate for the replacement of personnel. Groups that changed 1 or 2
players showed positive coordination transfer, but groups that changed 3
players did not. Nonlinear regression for temporal dynamics within verbalizing
groups showed asymptotic stability for initial coordination learning and
transfer to a difficult rule, a chaotic function when replacements were
introduced, and asymptotic stability again when the team with replacements
switched to the difficult rule. The dynamics for nonverbalizing groups were
similar. In the second experiment, 26 groups played a variation of the game
either verbally or nonverbally; there were no personnel replacements. The
effect of verbalization on coordination learning was replicated, but the
marginal value of verbalization dissipated over time. A questionnaire measured leadership emergence at the end of the
game along with other social contributions. The strength of leadership emergence
did not differ between verbal and nonverbal conditions, although differences in
other social contributions were observed. The probability distribution of
leadership ratings was consistent with current developments in nonlinear
dynamical systems theory. Most
nonlinear functions depicted the self-organization dynamics, but both a chaotic
and self-organizing function were observed in difficult coordination
situations.
Situativity of Learning within Groups:
Coevolutionary Dynamics Over Time Using Kauffman’s NK Model
Yu Yuan, University of Southern California
yuyuan@usc.edu
Bill McKelvey, UCLA
Rapid organizational learning capabilities are
critical in high velocity environments. Situativity learning theory holds that
contextually relevant communication interactivity is key to improved
organizational learning. We embellish situativity theory with ideas from the
study of complex adaptive systems, in particular Kauffman’s NK agent-based
model, somewhat altered (N = size; K = # of links among agents). We test nine
propositions that reflect nonlinear dynamic, multi-level, coevolutionary
processes, over time, that affect communication interactivity and the rate and
amount of organizational learning. Some are:
· Amount of group learning is a nonlinear nonmonotonic (inverted U)
function of K. · Rate of group learning
is a nonmonotonic function of increasing K and N. · Amount and rate of group learning is also a nonlinear
nonmonotonic (inverted U) function of the standardized measure of K, that is,
K/(N-1). The greater the differentiation
of communication ties toward stars and isolates, the lower the level of group
learning.
Our program docks with tables reported in
Kauffman (1993) with a correlation of 0.976. Some results are: As communication
interactivity becomes denser, and rate of learning speeds up, there are
diminishing returns to improving group learning supporting Kauffman’s
complexity catastrophe theory. After standardizing K by N-1, we find that the
catastrophe effect remains, but learning becomes a linear function of separate
variables increasing interactivity speeds up the rate of group learning, but it
diminishes the amount of learning. Altering the distribution of communication
stars and isolates has a
Rugged Landscapes and Complex Supply Networks
Kevin Dooley, Arizona State University
kevin.dooley@asu.edu
Tom Choi,
Arizona
State University
In many industries a majority of a product’s
value is added not by “final assemblers” (such as General Electric or General
Motors) but rather by suppliers, arranged in a complex web of
interconnectivity. These supply
networks are huge in size—for example, Daimer-Chrysler has 8000 “key”
suppliers—and have material and information flows that are not necessarily
simple and sequential. We shall apply Kauffman’s
rugged landscape model to better understand the dynamics of these supply
networks, with respect to their formation (supplier selection), and the design
and manufacture of products. In
particular, it appears there is a basic trade-off between simplicity of a
product or process design, as achieved by modularity, and the value embedded in
integral designs, which tend to add complexity to the management of the supply
network.
Nonlinear World of Dr. Suess
Terry Marks-Tarlow, Creativity Research Institute of Southern California
markstarlow@hotmail.com
This theoretical paper analyzes the children's
stories and visual images of Dr. Suess, whose fantastic universes have supplied
the early mental diet for generations of dynamical researchers. Fractals are evident in birds roosting upon
birds among other unusual beasts.
Horton Hears a Who reveals a critical bifurcation point, while the Cat
in the Hat illustrates paradoxical dynamics typical of psychological defenses.
Mapping Social Ecosystems
Ken Baskin, Life Design Partners
bman47@netaxs.com
This session will demonstrate a methodology for
mapping human complex adaptive systems, using the U.S. healthcare system as an
example. By focusing on relationships within any such system, this methodology
can help the mapper understand that any discrete piece of the system (a
regional system of professional healthcare providers, for example) is embedded
in a larger social context or "social ecosystem" (the network of
communities across that region). By recognizing the relationships throughout
such a social ecosystem, mappers also realize many leverage points (the
potential of the family in the health care process) that already exist and can
be used to improve the performance of these systems.
A Conversation on Emergence
Jeff Goldstein, Adelphi University
jegolds@attglobal.net
Topics: (a) theoretical strategies, (b)
discontinuity versus dissimilarity, (c) appropriate constructs and measures,
(d) self-transcending constructions as a new formalism for emergence, (e)
levels without hierarchy, (f) wholes without holism.
Sensemaking in teams: Does diversity affect the
ability of complex-adaptive systems to make sense
Brigitte
Fleeman, University of Texas at Austin,
b.fleeman@mail.utexas.edu
Using Weick’s (1995; 2001) framework of
sensemaking and the insights gained from research on complex-adaptive systems,
I am interested in empirically
investigating the question of whether and how differences among agents affect
the ability of organizations, as complex-adaptive systems, to make sense. In
general, diversity is a requisite and hallmark of complex adaptive systems. In
the organization literature, diversity is seen as both an asset as well as a
liability. On the one hand, diversity often leads to surprising and unique
inputs giving rise to novel and comprehensive considerations. On the other
hand, diversity can hinder organizational performance when multiple interpretations
must be understood and different cues integrated from a confusing array of
possibilities. This may add to the uncertainty and difficulty in making sense
together. In applying these perspectives to the interactions and relationships
in diverse groups, an interesting tension emerges: What levels of diversity and
differences are helpful in making sense together? What does the difference
among agents do to the ability of organizations as complex-adaptive systems to
make sense? Using a naturalistic
inquiry approach based on a constructivist paradigm (ethnographic methodology),
insights about dynamic patterns (Kelso, 1997) and complex adaptive systems
yielded from computer simulations (Axelrod, 1997; Holland, 1995; Kauffman,
1995) and philosophical considerations (Cilliers, 1998; Hardy, 1998; McDaniel
& Walls, 1997; Prigogine & Stengers, 1984; Waldrop, 1992), I will be
observing the process of sensemaking in less or more diverse teams (possible
setting: hospital).
The Dynamics of Local Rules in Hospital
Admission Processes
Beverly C.
Walker, bewalker@alphalink.com.au
Tim Haslett,
Monash
University
This paper reports on research into admission
practices at a hospital that provided sub acute extended care. A System Dynamics model of the patient flow
through the hospital was built to show the impact of the local rules used by
the medical registrar. Local rules are behaviours that are local, and often
idiosyncratic, adaptations to the local environment. Such adaptations can have
a significant impact on organisational performance. In the hospital, patients were admitted from two large acute
hospitals and from the community sources, into two different streams of care a
within the hospital. The process by which they were selected for admission set
up the dynamics of patient flows within the hospital. These dynamics involved the acuity of the patients and the
demands they placed on the medical systems within the hospital. Hospital funding in Victoria is based on
length of stay and occupancy rate. The
types and acuity of patients being admitted had a profound influence of these
funding bases. The local rules used by
the medical registrar, in turn, had a profound influence on the types of
patient being admitted. The System
Dynamics model demonstrated the impact of these local rules. During the process of building the model, it
became clear that neither the medical registrar, nor senior administrators
within the centre understood the impact of the local rules.
Is Chaos Research Normal Science?: Logical
Foundations of Postmodern Inquiry
M. Jayne
Fleener, University of Oklahoma
fleener@ou.edu
The first part of this presentation will
delineate the modernist mind-set and the inherent logic of domination
underlying modern science. Scientific,
social, and philosophical revolutions leading to process philosophies,
pragmatism, chaos theory, hermeneutics, and systems theory will be explored as
important seeds to the developing of Erwartungshorizonten, or the horizons of expectation
for a science of emergence and postmodern inquiry. The second part of the presentation will develop the logics of
relationship, meaning, and systems as postmodern inquiry. The logic of relationship has its modern
manifestation in the works of Whitehead and Dewey. Inquiry from a relational perspective will be explored as the
continuation of Poincare’s efforts and as the genesis of recursive and emergent
systems theories. The logic of meaning,
as found in Nietzsche and developed in Wittgenstein’s language games approach,
has implications for ideas about truth and the goals of inquiry. If meaning and truth cannot be provided
objective and certain foundations, reflecting a correlation between our
theories and some underlying reality, then how are we to interpret and
understand our goals of inquiry?
Finally, a logic of systems, coemerging with chaos dynamics, dissipative
structures, and post-Neo-Darwinism, together with the logics or relationship
and meaning, will be offered as perspectives from which a postmodern science
and approach to inquiry may proceed. The final portion of the presentation will
provide an example of the Mandelbrot set as an analytic tool to explore the
language games of a third grade mathematics classroom.
Using Complex Adaptive Systems Models for
Organizational Consulting
John Loveland Link
johnwlink@hotmail.com
Jo Lee Loveland Link
The co-authors, John and Jo Lee Loveland Link,
have been working in the field of chaos and complex adaptive systems as applied
to organizations since 1991. At that
time, the simulation now called Chaos,
Inc. was born an experiential non-computer-based full-day session engaged
participants in chaotic and dynamical events.
Without a prescribed agenda or outcomes, the simulation models real
business life. In addition, the authors
have integrated principles, practices, methodologies, and approaches that draw
on an understanding of complex adaptive systems (CAS) and apply them to
consulting interventions. This presentation
will provide highlights of the authors’ learning in regard to applications of
CAS concepts in organizational systems.
The focus will telescope on three organizational uses of CAS: diagnostic, descriptive, and
experiential. The authors will then
describe the chief emergent dynamics they see, based on their experiences and
experimental approaches. In addition,
the authors intend to use CAS
methodologies including discovery analysis and difference questioning, to
elicit participants’ insights and experiences regarding applications of CAS in
organizational life and potential opportunities to “morph” further evolutions.
The workshop will introduce some
basic concepts of complexity science.
First, we shall discuss the architecture of complex adaptive systems,
using Holland’s model: agents, fitness functions, behavioral rules, boundaries,
tags, connectivity and flow, and nonlinearity.
Next, some basic properties of complex systems will be discussed:
self-organization and emergence, self-organized criticality and power laws,
rugged landscapes, organizational dynamics, and social network theory. In the afternoon we shall discuss various
applications of these models, including examples in medical error, supply chain
management, organization change, and knowledge management. Emphasis will be on discussion, experiential
learning, and thoughts on how to move from concept to application.
Workshop: Nonlinear
Perspectives on Rhythm, Chaos, and Control in Human Biology: A Discussion of Theories and Methods
Robert Porter, Ph.D., Workshop
Coordinator, Directions for Mental Health (Clearwater FLA) & Lambda
Consulting (Tampa FLA); Franco Orsucci, M.D., Ph.D., Institute for Complexity Studies,
Rome, Italy; Dick Bird, Ph.D., U. of Northumbria, UK; Susan
Mirow, M.D., Ph.D., U. of Utah
Many nonlinear systems display
periodic, stochastic, chaotic, and continuously-adaptive behaviors. Nonlinear biological systems, including the
cardiopulmonary system, central nervous system, and the muscular-skeletal
system, display these behaviors. There
is a vast, classical, literature describing these biological systems and their
properties. How does a nonlinear
systems approach give us a clearer perspective on how these nonlinear systems
work, how they malfunction, or how they may be manipulated or repaired? In addition, what measurements and what
sorts of analysis do a nonlinear approaches demand? The workshop will address these questions using examples of data
collection and analysis from a variety of research areas. A focus of the
workshop will be the contrast between the more traditional
interpretations and the nonlinear ones.
This participatory workshop is designed for those scientists at an
intermediate-to-advanced level who (1) are interested in finding out more about
what is going on in other areas and who (2) are interested in discussing how
theoretical perspective informs research. A basic understanding of human
biology, nonlinear science, and research methods will be assumed. Enrollment limited to facilitate productive
discussion.
FINIS