Real-Time Search for Autonomous Agents and Multiagent Systems

Research output: Contribution to journalArticle

21 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)139-167
Number of pages29
JournalAutonomous Agents and Multi-Agent Systems
Volume1
Issue number2
DOIs
Publication statusPublished - 1998 Jan 1
Externally publishedYes

Fingerprint

Autonomous agents
Multi agent systems

Keywords

  • Autonomous agents
  • Multiagent systems
  • Real-time search

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Real-Time Search for Autonomous Agents and Multiagent Systems. / Ishida, Toru.

In: Autonomous Agents and Multi-Agent Systems, Vol. 1, No. 2, 01.01.1998, p. 139-167.

Research output: Contribution to journalArticle

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