Overview
- First book presenting a computational intelligence architecture capable of learning in unsupervised, supervised, or reinforcement learning modes
- The only book covering applications of time scales mathematics to engineering applications
- The only book which ties these learning paradigms into all three levels of intelligence and provides applications to engineering, markets, and society
Part of the book series: Adaptation, Learning, and Optimization (ALO, volume 6)
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Keywords
- Adaptive Resonance Theory
- Agent-Based Computational Social Science
- Approximate Dynamic Programming
- Backpropagation
- Backpropogation
- Computational Intelligence
- Dynamic Equations
- Game Theory
- Neural Network
- Reinforcement Learning
- Supervised Learning
- Time Scales Calculus
- Unsupervised Learning
- learning
- modeling
- complexity
Table of contents (7 chapters)
Authors and Affiliations
Bibliographic Information
Book Title: Unified Computational Intelligence for Complex Systems
Authors: John Seiffertt, Donald C. Wunsch
Series Title: Adaptation, Learning, and Optimization
DOI: https://doi.org/10.1007/978-3-642-03180-9
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2010
Hardcover ISBN: 978-3-642-03179-3Published: 01 July 2010
Softcover ISBN: 978-3-642-26395-8Published: 05 September 2012
eBook ISBN: 978-3-642-03180-9Published: 15 July 2010
Series ISSN: 1867-4534
Series E-ISSN: 1867-4542
Edition Number: 1
Number of Pages: 150
Number of Illustrations: 9 illustrations in colour
Topics: Artificial Intelligence, Computational Intelligence, Complexity, Economic Theory/Quantitative Economics/Mathematical Methods, Complex Systems, Statistical Physics and Dynamical Systems