A framework for the interleaving of execution and planning for dynamic tasks by multiple agents
The subject of multi-agent planning has been of continuing concern in Distributed Artificial Intelligence (DAI). In this paper, we suggest an approach to the interleaving of execution and planning for dynamic tasks by groups of multiple agents. Agents are dynamically assigned individual tasks that together achieve some dynamically changing global goal. Each agent solves (constructs the plan for) its individual task, then the local plans are merged to determine the next activity step of the entire group in its attempt to accomplish the global goal. Individual tasks may be changed during execution (due to changes in the global goal).
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.
KeywordsPlanning Process Multiple Agent Optimal Plan Heuristic Function Individual Task
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