1992 lectures in complex systems

書誌事項

1992 lectures in complex systems

editors, Lynn Nadel, Daniel Stein

(Santa Fe Institute studies in the sciences of complexity, Lectures ; v. 5)

Addison-Wesley Pub., c1993

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

}For five years the Complex Systems Summer School has contributed greatly to education and research into complex systems. 1992 Lectures in Complex Systems presents a wide array of topics in the field, including chaos, adaptive computation, neuronal oscillations, computational ecologies, the geometry of excitability, quenched disorder, biomolecular complexity, and nonlinear dynamics of social systems. This book is a compilation of many of the lectures and contributions of the 1992 Complex Systems Summer School. The collective volumes in the Series ( Lectures in the Sciences of Complexity, 1989 Lectures in the Sciences of Complexity, 1990 Lectures in Complex Systems, 1991 Lectures in Complex Systems, and now 1992 Lectures in Complex Systems ) comprise a growing, broad, interdisciplinary review of the many sciences of complexitya review unavailable elsewhere.Lectures included in This Volume:Melanie Mitchell: Genetic AlgorithmsCharles M. Gray: Rhythmic Activity in Neuronal Systems: Insights Into Integrative FunctionTad Hogg & Bernardo A. Huberman: Better than Best: The Power of CooperationA.T. Winifree: The Geometry of ExcitabilityJonathan S. Yedidia: Quenched Disorder: Understanding Classes Using a Variational Principle and the Replica MethodRobert H. Austin: Complexity in Biological MoleculesRaymond E. Goldstein: Nonlinear Dynamics of Pattern Formation in Physics and BiologyJoshua M. Epstein: On the Mathematical Biology of Arms Races, and Revolutions and An Adaptive Dynamic Model of Combat }

目次

  • Lecturers
  • Genetic Algorithms (Melanie Mitchell)
  • Rhythmic Activity in Neuronal Systems: Insights Into Integrative Function (Charles M. Gray)
  • Better Than the Best: The Power of Cooperation (Tad Hogg and Bernardo A. Huberman)
  • The Emergence of Computational Ecologies (Bernardo A. Huberman and Tad Hogg)
  • The Geometry of Excitability (A.T. Winfree)
  • Quenched Disorder: Understanding Classes Using a Variational Principle and the Replica Method (Jonathan S. Yedida)
  • Complexity in Biological Molecules (Robert H. Austin)
  • Nonlinear Dynamics of Pattern Formation in Physics and Biology (Raymond E. Goldstein)
  • On the Mathematical Biology of Arms Races, Wars, and Revolutions (Joshua M. Epstein)
  • An Adaptive Dynamic Model of Combat (Joshua M. Epstein)
  • Seminars
  • Chaos Concepts (E. Atlee Jackson)
  • Combining Generalizers by Using Partitions of the Learning Set (David H. Wolpert)
  • Large Fluctuations in Stochastically Perturbed Nonlinear Systems: Applications in Computing (Robert S. Maier)
  • On the Structural Complexity of Designed Systems (G. Yagil)
  • Global Information Systems and Nonlinear Methods in Crisis Management (Gottfried Mayer-Kress)
  • Student Contributions
  • Excursion Sets and a Modified Genetic Algorithm: Intelligent Slicing of the Hypercube (Subbiah Baskaran and David Noever)
  • Applying Genetic Algorithms to Improve EEG Classification and to Explore GA Parametrization (Cathleen Barczys, Laura Bloom, and Leslie Kay)
  • Symbiosis in Society and Monopoly in Nature: Mixed Metaphors from Biology and Economics (T. David Burns)
  • Disordered Models of Chemical Reactions in Complex Molecules (Igor Fedchenia and Billy Sundstrom)
  • A Game Theoretic Interpretation of the Spin Glass (Barry Feldman)
  • Lattice Games with Strategic Takeover (Barry Feldman and Kai Nagel)
  • Is There Room for Philosophy in the Science(s) of Complexity? (Brian L. Keeley and E. Bonabeau)
  • Animal Aggregation: Experimental Simulation by Using Vision-Based Behavioral Rules (Garry D. Peterson)
  • Learning of Passive Motor Control Strategies with Genetic Algorithms (Stefan Schaal and Dagmar Sternad)
  • How to Get A Biologists Guide to Internet Resources (U.R. Smith)
  • A Genetic Algorithm for Evolution from an Ecological Perspective{.

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