





. 
Complex
behavior can occur in any system made up of large numbers of
interacting constituents, be they atoms in a solid, cells in
a living organism, or consumers in a national economy.
Scientific theories about this behavior typically involve
many assumptions and approximations. Foundations of
Complexsystem Theories analyzes and compares, for the
first time, the key ideas and general methods used in
studying complexity in the physical, biological, and social
sciences. It highlights the features common to the three
areas, clarifies conceptual confusions, and provides a
nontechnical introduction to how we understand and deal with
complexity.
The
book begins with a description of the nature of complexity.
The author then examines a range of important concepts:
situated individuals, composite systems, collective
phenomena, emergent properties, chaotic dynamics, stochastic
processes. Each topic is illustrated by extended examples
from statistical physics, evolutionary biology, and
economics. What the sciences investigate are very
different, but how the sciences address their topics
has certain general commonality, which illustrates, among
other things, the general structure of our theoretical
reason.
Besides
the three sciences, the book also examines several
mathematical theories widely used in complexity research:
nonlinear and chaotic dynamics, the calculus of probability
and stochastic processes. It lays out the conceptual
structures of these mathematics and explains what make them
so powerful. By exposing the common conceptual foundation of
deterministic dynamics and stochastic processes, it refutes
both the doctrines of determinisim and chance.
This
detailed yet nontechnical book will appeal to anyone who
wants to know more about complex systems. It will also be of
great interest to philosophers engaged in scientific
methodology and specialists studying complexity in the
physical, biological, and social sciences. 







Contents 


 1. Introduction
 § 1. Synthetic
Microanalysis of Complex Systems
 § 2. Topics,
Theories, Categories
 § 3. Economics,
Evolutionary Biology, Statistical Physics
PART
I. EQUILIBRIUM
 2. Theories
of Composite Systems
 § 4. The World
in Many Levels of Description
 § 5. Deductive
Construction of Small Systems
 § 6. Synthetic
Microanalysis of Large Systems
 § 7.
Idealization, Approximation, Model
 § 8. Federal
Versus Imperial Unity of Science
 § 9.
Equilibrium and Optimization
 3.
Individuals: Systems and Constituents
 § 10. An
Individual and Its Possibilities
 § 11. The
Integrity of the Topic of Statistical Mechanics
 § 12. The Unit
of Evolution and the Unit of Selection
 § 13. Economic
Individuals as Ideal Optimizers
 4. Situated
Individuals and the Situation
 § 14.
IndependentIndividual Approximations
 § 15. Single
Particles in the SelfConsistent Field
 § 16. Price
Takers in the Competitive Market
 § 17. Fitness,
Adaptation, and the Environment
 5.
Interacting Individuals and Collective Phenomena
 § 18.
Intermediate Layers of Structure and Individuals
 § 19.
Collective Excitations and Their Coupling
 § 20. Economic
Institutions and Industrial Organization
 § 21.
Population Structure and the Evolution of Altruism
 6. Macro
Individuals and Emergent Properties
 § 22. Emergent
Characters of the System as a Whole
 § 23.
SelfOrganization in Phase Transition
 § 24.
AdaptiveOrganization of Biological Systems
 § 25.
Inflation, Unemployment, and Their Microfoundation
PART
II. DYNAMICS
 7. The
Temporality of Dynamic Systems
 § 26.
Temporality and Possibility
 § 27. Endurance
Versus Composition
 § 28. Past,
Present, Future
 8. The
Complexity of Deterministic Dynamics
 § 29.
Deterministic Dynamical Systems
 § 30.
Stability, Instability, Bifurcation
 § 31. Chaos and
Predictability
 § 32. Uniting
Deterministic and Stochastic Concepts
 § 33. The
Foundation of Statistical Mechanics
 § 34. Causality
but not Determinism
 9. Stochastic
Processes
 § 35. The
Calculus of Probability and Stochastic
 § 36.
Stochastic and Deterministic Models of Business Cycles
 § 37. The
Survival of the Fittest or the Luckiest?
 § 38. Causality
and Randomness in Statistical Mechanics
 § 39.
Probability but not Tychism
 10.
Directionality, History, Expectation
 § 40. Causality
and Temporally Asymmetry
 § 41. Natural
History and Its Abuse
 § 42. Dynamic
Optimization, Expectation, Uncertainty
 11. Epilogue
 § 43. A Look
Backward and Forward
 Notes
 Bibliography








