Complex Systems and Cognitive Processes
Published on 10. March 2012
Book
Paperback/Softback
X, 205 pages
978-3-642-46680-9 (ISBN)
Description
This volume describes our intellectual path from the physics of complex sys tems to the science of artificial cognitive systems. It was exciting to discover that many of the concepts and methods which succeed in describing the self organizing phenomena of the physical world are relevant also for understand ing cognitive processes. Several nonlinear physicists have felt the fascination of such discovery in recent years. 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. On the one hand, such artificial systems are important per se; on the other hand, it can be expected that their study will shed light on some general principles which are relevant also to biological cognitive systems. The main purpose of this volume is to show that nonlinear dynamical systems have several properties which make them particularly attractive for reaching some of the goals of artificial intelligence. The enthusiasm which was mentioned above must however be qualified by a critical consideration of the limitations of the dynamical systems approach. Understanding cognitive processes is a tremendous scientific challenge, and the achievements reached so far allow no single method to claim that it is the only valid one. In particular, the approach based upon nonlinear dynamical systems, which is our main topic, is still in an early stage of development.
More details
Edition
Softcover reprint of the original 1st ed. 1990
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
X, 205 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 12 mm
Weight
335 gr
ISBN-13
978-3-642-46680-9 (9783642466809)
DOI
10.1007/978-3-642-46678-6
Schweitzer Classification
Other editions
Additional editions
Roberto Serra | Gianni Zanarini
Complex Systems and Cognitive Processes
Book
02/1990
Springer
€117.69
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Persons
Roberto Serra is full professor of Complex Systems at the University of Modena and Reggio Emilia. He has previously been the Head of the Environmental Research Centre of the Montedison industrial group, the President of the Italian Association for Artificial Intelligence AI*IA and the Chairman of the Science Board of the European Centre for Living Technology. His main research interests, besides protocells, concern the dynamical modelling of Complex Systems, with applications to gene regulatory networks and cell differentiation, the analysis of their organization and the dynamical systems approach to Artificial Intelligence. He is the author or editor of eight books and of about 160 papers in international journals and conference proceedings with peer review.
Marco Villani is associate professor of Computer Science at the University of Modena and Reggio Emilia and a fellow of the European Centre for Living Technology. His main research interests, besides protocells, concern the dynamical modelling of Complex Systems, with applications to gene regulatory networks and cell differentiation, the analysis of their organization and the simulation of social systems. He is the editor of three books and of about 100 papers in international journals and conference proceedings with peer review.
Content
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.