Real-Time Search for Autonomous Agents and Multiagent Systems

Toru Ishida*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)139-167
Number of pages29
JournalAutonomous Agents and Multi-Agent Systems
Issue number2
Publication statusPublished - 1998
Externally publishedYes


  • Autonomous agents
  • Multiagent systems
  • Real-time search

ASJC Scopus subject areas

  • Artificial Intelligence


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