A heuristic technique for multi-agent planning

Eithan Ephrati*, Jeffrey S. Rosenschein

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

77 Scopus citations


The subject of multi-agent planning has been of continuing concern in Distributed Artificial Intelligence (DAI). In this paper, we suggest an approach to multi-agent planning that contains heuristic elements. Our method makes use of subgoals, and derived sub-plans, to construct a global plan. Agents solve their individual sub-plans, which are then merged into a global plan. The suggested approach reduces overall planning time and derives a plan that approximates the optimal global plan that would have been derived by a central planner, given those original subgoals. We explore three different scenarios. The first involves a group of agents with a common goal. The second considers how agents can interleave planning and execution when planning towards a common, though dynamic, goal. The third examines the case where agents, each with their own goal, can plan together to reach a state in consensus for the group. Finally, we consider how these approaches can be adapted to handle rational, manipulative agents.

Original languageAmerican English
Pages (from-to)13-67
Number of pages55
JournalAnnals of Mathematics and Artificial Intelligence
Issue number1-4
StatePublished - 1997


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