A Unified Framework based on HTN and POP for Approaches for Multi-Agent Planning
Abstract
The purpose of this paper is to introduce a multi-agent model for plan synthesis in which the production of a global shared plan is based on a unified framework based on HTN and POP approaches. In order to take into account agents' partial knowledge and heterogeneous skills, we propose to consider the global multi-agent planning process as a POP planning procedure where agents exchange proposals and counter-proposal. Each agent's proposal is produced by a relaxed HTN approach that defines partial plans in accordance with the plan space search planning, i.e., plan steps can contain open goals and threats. Agents' interactions define a joint investigation that enable them to progressively prune threats, solve open goals and elaborate solutions step by step. This distributed search is sound and complete.
Domains
Artificial Intelligence [cs.AI]
Origin : Files produced by the author(s)
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