Learning and Coordination: Enhancing Agent Performance through Distributed Decision Making by S.H. KimLearning and Coordination: Enhancing Agent Performance through Distributed Decision Making by S.H. Kim

Learning and Coordination: Enhancing Agent Performance through Distributed Decision Making

byS.H. Kim

Paperback | October 15, 2012

Pricing and Purchase Info

$247.50 online 
$288.50 list price save 14%
Earn 1,238 plum® points

Prices and offers may vary in store

Quantity:

In stock online

Ships free on orders over $25

Not available in stores

about

Intelligent systems of the natural kind are adaptive and robust: they learn over time and degrade gracefully under stress. If artificial systems are to display a similar level of sophistication, an organizing framework and operating principles are required to manage the resulting complexity of design and behavior.
This book presents a general framework for adaptive systems. The utility of the comprehensive framework is demonstrated by tailoring it to particular models of computational learning, ranging from neural networks to declarative logic.
The key to robustness lies in distributed decision making. An exemplar of this strategy is the neural network in both its biological and synthetic forms. In a neural network, the knowledge is encoded in the collection of cells and their linkages, rather than in any single component. Distributed decision making is even more apparent in the case of independent agents. For a population of autonomous agents, their proper coordination may well be more instrumental for attaining their objectives than are their individual capabilities.
This book probes the problems and opportunities arising from autonomous agents acting individually and collectively. Following the general framework for learning systems and its application to neural networks, the coordination of independent agents through game theory is explored. Finally, the utility of game theory for artificial agents is revealed through a case study in robotic coordination.
Given the universality of the subjects -- learning behavior and coordinative strategies in uncertain environments -- this book will be of interest to students and researchers in various disciplines, ranging from all areas of engineering to the computing disciplines; from the life sciences to the physical sciences; and from the management arts to social studies.
Title:Learning and Coordination: Enhancing Agent Performance through Distributed Decision MakingFormat:PaperbackDimensions:188 pagesPublished:October 15, 2012Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:9401044422

ISBN - 13:9789401044424

Look for similar items by category:

Reviews

Table of Contents

Preface. 1. Introduction and Framework. 2. Learning Speed in Neural Networks. 3. Principles of Coordination. 4. Case Study in Coordination. 5. Conclusion. Appendix: Dynamic Models in Statistical Physics. Index.