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Real-Time Search for Learning Autonomous Agents (Hardcover, 1997 ed.)
Loot Price: R4,571
Discovery Miles 45 710
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Real-Time Search for Learning Autonomous Agents (Hardcover, 1997 ed.)
Series: The Springer International Series in Engineering and Computer Science, 406
Expected to ship within 10 - 15 working days
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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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