Fast and Adaptive Multi-Agent Planning under Collaborative Temporal Logic Tasks via Poset Products.

ABSTRACT: Efficient coordination and planning is essential for large-scale multi-agent systems that collaborate in a shared dynamic environment. Heuristic search methods or learning-based approaches often lack the guarantee on correctness and performance. Moreover, when the collaborative tasks contain both spatial and temporal requirements, e.g., as linear temporal logic (LTL) formulas, formal methods provide a verifiable framework for task planning. However, since the planning complexity grows exponentially with the number of agents and the length of the task formula, existing studies are mostly limited to small artificial cases. To address this issue, a new planning paradigm is proposed in this work for system-wide temporal task formulas that are released online and continually. It avoids two comm

SUBMITTER: Liu Z 

PROVIDER: S-EPMC12326542 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature