Real-Time Search for Autonomous Agents and Multiagent Systems

Toru Ishida*

*この研究の対応する著者

研究成果: Article査読

24 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)139-167
ページ数29
ジャーナルAutonomous Agents and Multi-Agent Systems
1
2
DOI
出版ステータスPublished - 1998 1月 1
外部発表はい

ASJC Scopus subject areas

  • 人工知能

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