Real-Time Search for Learning Autonomous Agents: 406 (The Springer International Series in Engineering and Computer Science, 406) - Tapa dura

Ishida, Toru

 
9780792399445: Real-Time Search for Learning Autonomous Agents: 406 (The Springer International Series in Engineering and Computer Science, 406)
Tapa dura
ISBN 10: 0792399447 ISBN 13: 9780792399445
Editorial: Springer, 1997

Sinopsis

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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Reseña del editor

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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Editorial
Springer
Año de publicación
1997
Idioma
Inglés
ISBN 10 
0792399447
ISBN 13 
9780792399445
Encuadernación
Tapa dura
Número de páginas
148
Contacto del fabricante
no disponible
Persona responsable
CMN Printpool Inh. Mathis Neumann
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

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Hamburg
Alemania

Otras ediciones populares con el mismo título

9781475770643: Real-Time Search for Learning Autonomous Agents: 406 (The Springer International Series in Engineering and Computer Science)

Edición Destacada

ISBN 10:  1475770642 ISBN 13:  9781475770643
Editorial: Springer, 2013
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