Real-Time Search for Learning Autonomous Agents

Name: Real-Time Search for Learning Autonomous Agents
Brand: Springer
SKU: 9780792399445
Price: 3938 CZK
Availability: InStock

Autor: Toru Ishida

Jazyk:

Vazba: Pevná

Vydavatel: Springer

Dostupnost: Skladem u dodavatele v malém množství

Odesíláme za 13-18 dnů

3 938 Kč

Autonomous agents or multiagent systems are computational systems in which several computational age...

Informace o knize

Autor

Toru Ishida

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

1997

Stránek

126

EAN

9780792399445

ISBN

0792399447

Enbook ID

01398552

Vydavatel

Springer

Hmotnost

860

Rozměry

155 x 235 x 10

Kompletní popis

Autonomous agents or multiagent systems are computational systems in which several computational agents interact or work together to perform some set of tasks. These systems may involve computational agents having common goals or distinct goals. Real-Time Search for Learning Autonomous Agents focuses on extending real-time search algorithms for autonomous agents and for a multiagent world. Although real-time search provides an attractive framework for resource-bounded problem solving, the behavior of the problem solver is not rational enough for autonomous agents. The problem solver always keeps the record of its moves and the problem solver cannot utilize and improve previous experiments. Other problems are that although the algorithms interleave planning and execution, they cannot be directly applied to a multiagent world. The problem solver cannot adapt to the dynamically changing goals and the problem solver cannot cooperatively solve problems with other problem solvers. This book deals with all these issues. Real-Time Search for Learning Autonomous Agents serves as an excellent resource for researchers and engineers interested in both practical references and some theoretical basis for agent/multiagent systems. The book can also be used as a text for advanced courses on the subject.

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Real-Time Search for Learning Autonomous Agents

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