Résumé
Traditional methods for creating intelligent computational
systems haveprivileged private "internal" cognitive and
computational processes. In contrast, Swarm Intelligence:
Collective Adaptation argues that human intelligence
derives from the interactions of individuals in a social
world and further, that this model of intelligence can be
effectively applied to artificially intelligent systems.
The authors first present the foundations of this new
approach through an extensive review of the critical
literature in social psychology, cognitive science, and
evolutionary computation. They then show in detail how
these theories and models apply to a new computational
intelligence methodology— particle swarms—which
focuses on adaptation as the key behavior of intelligent
systems. Drilling down still further, the authors describe
the practical benefits of applying particle swarm
optimization to a range of engineering problems. Developed
by the authors, this algorithm is an extension of cellular
automata and provides a powerful optimization, learning,
and problem solving method.
This important book presents valuable new insights by exploring the boundaries shared by cognitive science, social psychology, artificial life, artificial intelligence, and evolutionary computation and by applying these insights to the solving of difficult engineering problems. Researchers and graduate students in any of these disciplines will find the material intriguing, provocative, and revealing as will the curious and savvy computing professional.
Features
- Places particle swarms within the larger context of intelligent adaptive behavior and evolutionary computation.
- Describes recent results of experiments with the particle swarm optimization (PSO) algorithm
- Includes a basic overview of statistics to ensure readers can properly analyze the results of their own experiments using the algorithm.
- Support software which can be downloaded from the publishers website, includes a Java PSO applet, C and Visual Basic source code.
- Introduction
- Part 1: Foundations
- Life and Intelligence
- Optimization by Trial and Error
- On our Nonexistence as Entities
- Evolutionary Computation Theory and Paradigms
- Humans - Actual, Imagined and Implied
- Thinking is Social
- Part 2: Particle Optimization and Collective Intelligence
- The Binary Particle Swarm
- Variations and Comparisons
- Applications
- Implications and Speculations
- Conclusions
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Morgan Kaufmann |
| Auteur(s) | Russell C. Eberhart, James Kennedy |
| Parution | 01/04/2001 |
| Nb. de pages | 512 |
| Format | 19 x 24 |
| Couverture | Relié |
| Poids | 1111g |
| Intérieur | Noir et Blanc |
| EAN13 | 9781558605954 |
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