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 |
|---|---|
| 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 |
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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 journal › Article
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TY - JOUR
T1 - Real-Time Search for Autonomous Agents and Multiagent Systems
AU - Ishida, Toru
PY - 1998/1/1
Y1 - 1998/1/1
N2 - 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.
AB - 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.
KW - Autonomous agents
KW - Multiagent systems
KW - Real-time search
UR - http://www.scopus.com/inward/record.url?scp=0032182881&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0032182881&partnerID=8YFLogxK
U2 - 10.1023/A:1026449201026
DO - 10.1023/A:1026449201026
M3 - Article
VL - 1
SP - 139
EP - 167
JO - Autonomous Agents and Multi-Agent Systems
JF - Autonomous Agents and Multi-Agent Systems
SN - 1387-2532
IS - 2
ER -