1 Introductory Concepts --;1.1 Complex Systems and Self-organization --;1.2 Self-organization in Artificial Systems --;1.3 Cognitive Processes in Artificial Systems --;1.4 Metaphors of the Cognitive Sciences --;2 The Dynamical Systems Approach to Artificial Intelligence --;2.1 Introduction --;2.2 Dynamical Systems, Attractors and Meaning --;2.3 Neural Networks --;2.4 The Relationship with Classical AI --;3 Dynamical Behaviour of Complex Systems --;3.1 Introduction --;3.2 One-Dimensional Dynamical Systems --;3.3 Two-Dimensional Dynamical Systems --;3.4 Cellular Automata --;3.5 The Life Game --;3.6 Random Boolean Networks --;3.7 Computation in Reaction-Diffusion Systems --;4 Homogeneous Neural Networks --;4.1 Introduction --;4.2 The Hopfield Model --;4.3 Modifications of the Hopfield Model --;A4.1 Non-Deterministic Dynamics of the Model --;A4.2 Memorization and Recognition of Two States --;5 Network Structure and Network Learning --;5.1 Introduction --;5.2 Layered Networks --;5.3 Back-Propagation Algorithms --;5.4 Self-organization and Feature Extraction --;5.5 Learning in Probabilistic Networks --;5.6 Unsupervised Learning --;A5.1 The Learning Algorithm for the Boltzmann Machine --;6 Dynamical Rule Based Systems --;6.1 Introduction --;6.2 Classifier Systems and Genetic Algorithms --;6.3 The Equations of Classifier Systems --;6.4 The Dynamics of Classifier Systems --;6.5 Classifier Systems and Neural Networks --;A6.1 Implicit Parallelism --;7 Problems and Prospects --;7.1 Introduction --;7.2 Knowledge Representation --;7.3 The Role of Dynamics --;7.4 On the Limits of the Dynamical Approach --;References.
SUMMARY OR ABSTRACT
Text of Note
This volume describes our intellectual path from the physics of complex sys- tems to the science of artificial cognitive systems. In this volume, we will limit our discussion to artificial cognitive systems, without attempting to model either the cognitive behaviour or the nervous structure of humans or animals.