Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them.
How do social structures and group behaviors arise from the interaction of individuals? Growing Artificial Societies approaches this question with cutting-edge computer simulation techniques. Fundamental collective behaviors such as group formation, cultural transmission, combat, and trade are seen to "emerge" from the interaction of individual agents following a few simple rules.
Catching Ourselves in the Act uses situated robotics, ethology, and developmental psychology to erect a new framework for explaining human behavior. Rejecting the cognitive science orthodoxy that formal task-descriptions and their implementation are fundamental to an explanation of mind, Horst Hendriks-Jansen argues for an alternative model based on the notion of interactive emergence.
Scientists and philosophers are focusing more intensely than ever on the nature of our human experience, resulting in a newly coalescing field of Consciousness Studies that has become a worldwide and highly interdisciplinary phenomenon.
Comparative Approaches to Cognitive Science consolidates a series of recent advances in cognitive science, describing a novel, animal-based, largely nonsymbolic approach to understanding basic mechanisms in adaptive intelligence.
Evolutionary programming is one of the predominate algorithms withing the rapidly expanding field of evolutionary computation. These edited contributions to the Fourth Annual Conference on Evolutionary Programming are by leading scientists from academia, industry, and defense. The papers describe both the theory and practical application of evolutionary programming, as well as other methods of evolutionary computation including evolution strategies, genetic algorithms, genetic programming, and cultural algorithms.
Artificial life, a field that seeks to increase the role of synthesis in the study of biological phenomena, has great potential, both for unlocking the secrets of life and for raising a host of disturbing issues—scientific and technical as well as philosophical and ethical.
Genetic Programming II extends the results of John Koza's ground-breaking work on programming by means of natural selection, described in his first book, Genetic Programming. Using a hierarchical approach, Koza shows that complex problems can be solved by breaking them down into smaller, simpler problems using the recently developed technique of automatic function definition in the context of genetic programming.
Intelligence takes many forms. This exciting study explores the novel insight, based on well-established ethological principles, that animals, humans, and autonomous robots can all be analyzed as multi-task autonomous control systems. Biological adaptive systems, the authors argue, can in fact provide a better understanding of intelligence and rationality than that provided by traditional AI.
More than sixty contributions in From Animals to Animats2 by researchers in ethology, ecology, cybernetics, artificial intelligence, robotics, and related fields investigate behaviors and the underlying mechanisms that allow animals and, potentially, robots to adapt and survive in uncertain environments. Jean-Arcady Meyer is Director of Research, CNRS, Paris. Herbert L. Roitblat is Professor of Psychology at the University of Hawaii at Manoa. Stewart W. Wilson is a scientist at The Rowland Institute for Science, Cambridge, Massachusetts.
Genetic programming may be more powerful than neural networks and other machine learning techniques, able to solve problems in a wider range of disciplines. In this ground-breaking book, John Koza shows how this remarkable paradigm works and provides substantial empirical evidence that solutions to a great variety of problems from many different fields can be found by genetically breeding populations of computer programs. Genetic Programming contains a great many worked examples and includes a sample computer code that will allow readers to run their own programs.
Genetic algorithms are playing an increasingly important role in studies of complex adaptive systems, ranging from adaptive agents in economic theory to the use of machine learning techniques in the design of complex devices such as aircraft turbines and integrated circuits. Adaptation in Natural and Artificial Systems is the book that initiated this field of study, presenting the theoretical foundations and exploring applications.
Artificial life embodies a recent and important conceptual step in modem science: asserting that the core of intelligence and cognitive abilities is the same as the capacity for living. The recent surge of interest in artificial life has pushed a whole range of engineering traditions, such as control theory and robotics, beyond classical notions of goal and planning into biologically inspired notions of viability and adaptation, situatedness and operational closure.
These sixty contributions from researchers in ethology, ecology, cybernetics, artificial intelligence, robotics, and related fields delve into the behaviors and underlying mechanisms that allow animals and, potentially, robots to adapt and survive in uncertain environments. They focus in particular on simulation models in order to help characterize and compare various organizational principles or architectures capable of inducing adaptive behavior in real or artificial animals.