Titlebook: Networks of Learning Automata; Techniques for Onlin M. A. L. Thathachar,P. S. Sastry Book 2004 Kluwer Academic Publishers 2004 Computer Vis

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Introduction,d earlier mostly by psychologists, has become a topic of much interest to engineers as well, in view of its role in machine intelligence. Psychologists or biologists who conduct learning experiments on animals or human subjects try to create models of behavior through analysis of experimental data.

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Parallel Operation of Learning Automata,perate in slowly varying environments and the learning process should be completed well before significant changes take place in the environment; otherwise, learning is ineffective. In the case of learning automata algorithms, speed of convergence can be increased by increasing the value of the lear

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Epilogue,ting their action probability distributions in accordance with the reinforcement obtained from the environment. In Chapter 1 we have considered a variety of LA to suit different situations. Chapters 2 and 3 described how collections of LA could be formed into teams and networks to solve more complex

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Manish L. Raorane,Joan O. Narciso,Ajay Kohliunder which symbolic representation of knowledge (as rules or frames) or purely statistical approaches are likely to be more useful in building decision aids. Since the utility of a decision support system is a combined function of both the cost of system development and the change in performance of

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Decision-Making for Flood-Threatened Propertiesindividual property? ? Reducing recovery duration: should property components be removed from the property before the flood, replaced after the flood, or dried and cleaned after the flood? ? Implementing resilient reinstatement: resilient reinstatement should be a social, not property-orientated, so

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