Real-Time Search for Autonomous Agents and Multiagent Systems

Since real-time search provides an attractive framework for resource-bounded problem solving, this paper extends the framework for autonomous agents and for a multiagent world. To adaptively control search processes, we propose ␧-search which allows suboptimal solutions with ␧ error, and ␦-search which balances the tradeoff between exploration and exploitation. We then consider search in uncertain situations, where the goal may change during the course of the search, and propose ( ) ( )a mo¨ing target search MTS algorithm. We also investigate real-time bidirectional search RTBS algorithms, where two problem solvers cooperatively achieve a shared goal. Finally, we introduce a new problem solving paradigm, called organizational problem sol¨ing, for multiagent systems.

• Type: Journal
• Year: 1998
• Where: AAMAS
• Authors: Toru Ishida
• Keywords: AAMAS 1998, Attractive Framework, Intelligent Agents, Real-time Search, Resource-bounded Problem