Titlebook: Real-Time Search for Learning Autonomous Agents; Toru Ishida Book 1997 Springer Science+Business Media New York 1997 agents.algorithms.aut

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0893-3405 ome set of tasks. These systems may involvecomputational agents having common goals or distinct goals. ..Real-Time Search for Learning Autonomous Agents. focuses onextending real-time search algorithms for autonomous agents and for amultiagent world. Although real-time search provides an attractivef

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Book 1997 tasks. These systems may involvecomputational agents having common goals or distinct goals. ..Real-Time Search for Learning Autonomous Agents. focuses onextending real-time search algorithms for autonomous agents and for amultiagent world. Although real-time search provides an attractiveframework f

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Cooperating in Uncertain Situations, knows its current location in the maze, and can communicate with the other robot; thus, each robot always knows its goal location. Even though the robots do not have a map of the maze, they can gather information around them through various sensors.

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Realtime Search Performance,exact cost to the goal along the optimal path to the goal. However, there is almost no research on the learning efficiency of realtime search. This chapter is intended to evaluate the learning process to clarify the following three basic questions [Mizuno and Ishida, 1995].