Unified Computational Intelligence for Complex Systems

Front Cover
Springer Science & Business Media, Jul 15, 2010 - Computers - 150 pages
Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to erect suspension bridges, although both are products of technological advancement and reflect an increased understanding of our world. In this book, we show how to unify aspects of learning and adaptation within the computational intelligence framework. While a number of algorithms exist that fall under the umbrella of computational intelligence, with new ones added every year, all of them focus on the capabilities of learning, adapting, and helping us seek. So, the term unified computational intelligence relates not to the individual algorithms but to the underlying goals driving them. This book focuses on the computational intelligence areas of neural networks and dynamic programming, showing how to unify aspects of these areas to create new, more powerful, computational intelligence architectures to apply to new problem domains.
 

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Contents

Introduction
1
The Unified Art Architecture
18
An Application of Unified Computational Intelligence
33
The Time Scales Calculus
49
Approximate Dynamic Programming on Time Scales
61
Backpropagation on Time Scales
77
Unified Computational Intelligence in Social Science
91
References
110
Copyright

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