Complexity/Dynamical Systems Annotated Bibliography in Progress
15 December 2000 Version
With thanks to Joe McGrath and to the members of the Fall 2000 Complexity seminar at the
University of Oregon, who contributed some of the titles and commentary. To add to the list, e-mail Holly Arrow at email@example.com.
Abraham, F. D., Abraham, R. H., & Shaw, C. S. (1990). A visual
dynamical systems theory for psychology. Santa Cruz, CA: Aerial Press.
First part presents basic concepts of mathematical dynamics with
pictures of phase portraits,
buckling columns, etc. Second part gives examples of concepts applied to psychological
phenomena -- family conflict, approach-avoidance, and neurological
Arrow, Holly, & Crosson, Scott B. (2000, under revision) Musical chairs: Membership
choice and change in self-organized groups.
Looks at group size as an evolving
global variable in repeated sessions of self-organized group
formation in which groups earn money that they divide amongst their membership. Analysis of
transition probabilities over time indicates that the inclusion of extra, unnecessary group
members is a broad, stable attractor when those left out earn no money, but this attractor
disappears when people left out are given a small "welfare" payment. Illustrates a low-tech
application of dynamic systems approaches to short time
Arrow, H., McGrath, J. E.,& Berdahl, J. L. (2000). Small groups as complex systems:
Formation, coordination, development, and adaptation. Newbury Park, CA: Sage.
High concept, low tech theory piece
integrating the ideas of dynamical systems and complexity
theory into the study of small groups. Includes a discussion of methodological and philosophy of
science issues but does not provide step-by-step how-to
Boisot, M., & Child, J. (1999). Organizations as adaptive systems in complex
environments: The case of China. Organization Science, 10 (3), 237-252.
Conceptual article proposing a three
dimensional model for understanding environmental
complexity by looking at information. Two dimensions (codification and abstraction) measure
cognitive complexity; the third (diffusion of information) measures relational complexity. B&C
propose that organizations cope with environmental complexity by either absorbing or reducing
it, and apply these ideas to Western firms operating in China, which has high low cognitive
complexity, high relational complexity within societal units, and low relational complexity
between societal units. Complexity ideas are fully integrated into
Briggs, J. & Peat,
F. D. (1989). Turbulent mirror: An illustrated guide to chaos theory
and the science of wholeness. New York: Harper & Row.
Very readable introduction to chaos
theory, catastrophe theory, complexity, fractals, etc. Basic
theme is how order leads to chaos and vice versa. Relates chaos to quantum theory and
Bruderer, E. & Singh, J. V. (1996). Organizational evolution, learning, and selection: A
genetic-algorithm-based model. Academy of Management Journal, 39 (5), 1322-1349.
Integrates three processes of
organizational change in a single model: (1) organizational learning,
analogous to change and adaptation within the lifetime of an organism (2) organizational
variation as new organizational forms are created and (3) selection of organizations by the
marketplace, with unfit forms going out of business. Simulation data from the genetic algorithm
indicates that in a fixed fitness landscape with a single fitness "spike," organizational learning is
effective in finding new and effective forms. In a hill-like landscape, inert organizational forms
created by variation and selection are more effective.
Cambel, A. B. (1993). Applied Chaos Theory: A paradigm for Complexity. San
Diego, CA: Academic Press.
Casti, J. L. (1994). Complexification: Explaining a paradoxical world through the
science of surprise. New York: Harper Collins.
In each chapter Casti tackles a basic
intuition we have (e.g., small changes should have small
effects) and then elaborates the mathematics underlying phenomena that violate this intuition
(e.g., catastrophe theory).
Cohen, Jack, & Stewart, Ian (1994). The collapse of chaos. New York & London:
The first half reviews the findings of
the accepted scientific data base, providing a quick review
of chemistry, physics, biology, neuroscience, computer science, and social science through the
lens of a reductionist approach. The second half returns to these topics taking a complex systems
approach to quantum theory, evolution, chemical reactions, artificial life, consciousness and
perception. Includes an annotated "further reading" list.
Crutchfield, J. P., Farmer, J. D.,
Packard, N. H., & Shaw, R. S. (1986) Chaos. Scientific American, 255 (December), 46-57.
These four physicists comprised the
Dynamical Systems Collective at Santa Cruz, who
encountered chaotic dynamics in the operation of an analog computer and in the time sequence of
Eidelson, R. J. (1997). Complex adaptive systems in the behavioral and social sciences.
Review of General Psychology, 1, 42-7.
Good introduction to the
characteristics of complex systems such as multiple hierarchical levels,
self-organization, positive feedback, bifurcations, cusp catastrophes, hysteresis, and coevolution,
illustrated throughout with examples of how these ideas are being applied in psychology,
sociology, economics, and political science.
Gilbert, Nigel, & Troitzsch, Klaus G. (1999). Simulation for the social scientist.
Buckingham, England, & Philadelphia, PA: Open University Press.
Detailed review of different simulation
techniques, including discussion of examples from social
sciences, sample programs, list of useful web
Gleick, J. (1987). Chaos: Making a new science. New York: Viking Penguin.
Organized as a series of stories about
American contributors to chaos, with lots of human interest
bibliographical details. Underlying theme is that chaos theory represents a Kuhnian "paradigm
Gottman, J. M., Guralnick, M. J., Wilson, B., Swanson, C. C., & Murray, J. D. (1997).
What should be the focus of emotion regulation in children? A nonlinear dynamic mathematical
model of children's peer interaction in groups. Development and Psychopathology, 9, 421-452.
Presents a mathematical model of mutual
influence between an individual and a group, with the
group represented by whoever the focal individual is interacting with at a given point. The model
is then tested using data from children's play groups, some of which included children with
developmental delays or language disorders. Results are presented as step functions. Graphs and
explanations often hard to follow, but paper presents an intriguing strategy for studying ordinal
data on mutual influence, decomposed into influence of child on the group
& group on the child.
Gregson, R.A.M., Pressing, J. L. (2000). Dynamic modeling. In J. T. Ccioppo, L. G.
Tassinary, & G. G. Berntson (Eds.), Handbook of
2nd ed. (pp. 924-948). New
York: Cambridge University Press.
A dense, thorough overview of how to
model and analyze physiological data, including transition
matrices, a variety of dimensionality measures, the use of embedding procedures, Lyapunov
coefficients, and measures of entropy. G& P provide and explain equations, illustrate the
techniques using EEG data, and address issues about measurement quality and the necessary
number of data points to conduct various analyses. Includes a useful
glossary of technical terms.
Kauffman , Stuart A. (1993). The Origins of Order: Self-organization and Selection in
Evolution. Univ. of Pennsylvania and the Santa Fe Institute: Oxford University Press
A large dense book on self-organization,
selection, and adaptation in developmental and
evolutionary biology. Includes detailed exposition of rugged fitness landscapes, random graphs,
hypercycles, and Kauffman's ideas about "order for free." Pretty tough
Kellert, S. H. (1993). In the wake of chaos. Chicago: The University of Chicago Press.
Excellent discussion of the implications
of chaos theory for the philosophy of science. Also
discusses the neglect of nonlinear phenomena from a sociopolitical point of view, drawing upon
the insights of feminist scholars such as Keller, Harding, and
Kelso, J. A. S. (1995). Dynamic patterns: The self-organization of brain and behavior.
Cambridge, MA: MIT Press.
Lange, R. (1999). A cusp catastrophe approach to the prediction of temporal patterns in
the kill dates of individual serial murderers. Nonlinear Dynamics,
Psychology, and Life
Sciences, 3 (2), 143-159.
Demonstrates that a cusp catastrophe
model fits the time series data of 11 murderers much better
than linear models. The authors use Guastello's equations for the cusp model, and are able to
classify the time series into three dynamic patterns, showing an attractor, a repellor, or a "pulse"
pattern. Lots of visuals, many points of methodology not well explained. Shows that catastrophe
approach can be employed even with quite short time series for limited
number of subjects.
Lewin, Roger.(1992). Complexity: Life at the Edge of Chaos. New York: Macmillan
Good broad introduction to complexity by
a science writer based on conversations with dozens
of British and American scientists including James Lovelock, Brian Goodwin, John Maynard
Smith, Steven Jay Gould, Edward O. Wilson, Chris Langton.
Lewis, M. D. (2000). The promise of dynamic systems approaches for an integrated
account of human development. Child Development, 71 (1), 35-43.
Presents developmental psychology as a
fragmented field that might be united by focusing on
self-organization as an general principle that can be applied to understanding change and novelty.
Describes core concepts in dynamical systems thinking, such as far from equilibrium systems,
abrupt phase transitions, and increasing complexity over
Lewis, Marc D., Lamey, Alex V., & Douglas, Lori. (1999). A new dynamic systems
method for the analysis of early socioemotional development. Developmental Science 2 (4), 457-475.
Illustrates the construction of state
space grids for ordinal data, the identification of fixed point
attractors, and the measurement of basin strength and relaxation time for these attractors, using
data on gaze angle and distress of infants during multiple sessions at 2 months and 6 months old.
The method is used to look both at similarities within age groups and individual differences
among the infants.
Marken, R. S. (1990). Purposeful Behavior: The Control Theory Approach. American
Behavioral Scientist, 34, No. 1 [Special Issue].
Contains 15 articles dealing with
aspects of control theory. The authors include Powers, Runkel,
Newtson, Darren (1994). The perception and coupling of behavior waves. In R. R.
Vallacher & A. Nowak (Eds.), Dynamical systems in social psychology (pp. 139-167). New
York: Academic Press.
Looks at the perception of human action
using change in joint angles, decomposing the resulting
data stream using spectral analysis. Also reports work on the dynamic coupling of gestures and
vocal intensity in interacting dyads. Some of the concepts and graphics are rather hard to follow,
but the chapter is full of provocative ideas.
Nowak, Szamrej, & Latané (1990). From private attitude to public opinion: A dynamic
theory of social impact. Psychological Review, 97, 362-376.
Computer simulation of attitude change
based on dynamic social impact theory, using a cellular
Prigogine I. C. & Stengers, I. (1984). Order out of chaos: Man's new dialogue with
nature. NY: Bantam Books.
Prigogine won the Nobel Prize in
chemistry in 1977. Stengers is a philosopher, chemist, and
historian of science. This beautifully written book contrasts the science of the 17th through 19th
century, with its emphasis on stability, order, uniformity, and equilibrium, with the emerging 20th
century view of the world that emphasizes fluctuation, turbulence, instability, and far from
Rosen, R. (1979) Sixth Annual Ludwig von Bertalanffy Memorial Lecture. Behavioral
Science, 24 (4), 238-249.
Excellent article on general systems
theory as it applies to biological systems, discusses some
contrasts between that theory and earlier Newtonian ones.
Schwartz, J. (1999). Oh my Darwin! Lingua Franca (November), 14-21.
Journalistic piece discussing the
intellectual conflicts between Steven Pinker and Steven Jay
Gould, with additional discussion of the ideas of Bill Hamilton, Richard Dawkins, Richard
Lewontin and E.O. Wilson, framed as a conflict between sociobiology/evolutionary psychology
and punctuated equilibrium theory. The description of who is in what camp and who dislikes
whom is clearer than the explanation of what, exactly, are the
intellectual points of disagreement.
Sawada, D. & Caley, M. T. (1985) Dissipative structures: New metaphors for becoming
in education. Educational Researcher 14 (3), 13-19.
They use Prigogine's ideas about
dissipative structures -- self-organizing systems far from
equilibrium -- as the central idea for how we should think about
Vallacher, R. R., & Nowak, A. (1994). The chaos in social psychology. In R. R.
Vallacher & A. Nowak (Eds.), Dynamical systems in social psychology (pp. 1-16). New York:
I like this article because it
articulates my own dissatisfaction with the state of social psychology.
Diagnoses the key problems of social psychology as fragmentation, conceptual incoherence,
proliferation of multiple mini-theories to explain every conceivable phenomena, ill-defined
topics, and the lack of integrating metatheories that allow us to make some sense out of this
mess. Optimistic interpretations of this state of affairs are considered and rejected, and a
dynamical systems perspective is prescribed as an integrating meta-theory that will also turn the
attention of social psychologists to a more serious treatment of time and complexity. Waldrop, M. M. (1992). Complexity: The emerging science at the edge of order and
Waldrop, M. M. (1992). Complexity: The emerging science at the
edge of order and chaos. New York: Simon & Schuster.
Presents contributions to complexity
theory, the new umbrella term for the intersection of chaos
theory, neural nets, AI, developments in evolutionary biology, and so on. Main focus is on
researchers connected to the Santa Fe Institute.