2003 · 41 citations · 16 references
ComputingAutonomous SystemsComputer ScienceArtificial IntelligenceDistributed SystemsMulti-robot SystemsIntelligent AgentsMulti-agent SystemsMulti-robot CoordinationAgent CoordinationAgent PlanningHierarchical Task PlanningMulti-agent Decision MakingMulti-agent PlanningMultiagent ControlStructured Representations
It is critical for agents in a multiagent environment to avoid interfering with each other when carrying out their tasks. However, to avoid execution inefficiencies, they also should capitalize on cooperative opportunities. In state oriented domains [14], identifying overlapping effects between agents' plans enables some agents to leave some tasks to others, thereby reducing the cost of execution and improving the overall efficiency of the multiagent system. This is what we term synergy. In this paper, we define criteria for finding a certain type of synergy involving agents with overlapping goals. We also develop algorithms for discovering this synergy between planning agents that exploit hierarchical plan representations. Our results show that our approach not only can reduce the costs of finding synergies compared to non-hierarchical strategies, but can also find synergies that might otherwise be missed.
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An analysis of time-dependent planning
Thomas Dean, Mark Boddy · National Conference on Artificial Intelligence · 1988 · 778 citations
Constraint propagation algorithms for temporal reasoning
Marc Vilain, Henry Kautz · 1986 · 643 citations
NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE
Washington Hilton · 1983 · 373 citations
Planning as search: A quantitative approach
Richard E. Korf · Artificial Intelligence · 1987 · 368 citations