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Real-Time Search for Autonomous Agents and Multiagent Systems

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Abstract

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 ε-search which allows suboptimal solutions with ε error, and δ-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 moving 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 solving, for multiagent systems.

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Authors and Affiliations

  1. Department of Social Informatics, Kyoto University, Japan

    Toru Ishida

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  1. Toru Ishida
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Ishida, T. Real-Time Search for Autonomous Agents and Multiagent Systems. Autonomous Agents and Multi-Agent Systems 1, 139–167 (1998). https://doi.org/10.1023/A:1026449201026

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