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 language | English |
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Pages (from-to) | 139-167 |
Number of pages | 29 |
Journal | Autonomous Agents and Multi-Agent Systems |
Volume | 1 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1998 Jan 1 |
Externally published | Yes |
Keywords
- Autonomous agents
- Multiagent systems
- Real-time search
ASJC Scopus subject areas
- Artificial Intelligence