A Hyper-Logical View on Multi-Agent Path Planning

arXiv:2610.35964v1 Announce Type: cross Abstract: Multi-Agent Path Planning (MAPP) requires collision-free paths for multiple agents. MAPP has numerous real-life applications, including the navigation of automated vehicles, and has therefore many variants considering different constraints, requirements, and objectives. For each such variant, a new algorithmic treatment is often developed. This paper takes a complementary, specification-centered view: we show that many MAPP variants can be modeled in HyperLTL, a temporal logic that reasons about multiple paths and their evolution through time, and in its omega-regular extension HyperQPTL. The contribution is not a claim that current hyperproperty model checkers replace specialized MAPP solvers. Rather, the hyper-logical view gives a unified language for comparing MAPP variants, adding cross-agent constraints, expressing optimality, and connecting MAPP to verification, explanation, and causality techniques for hyperproperties.

Related

• Scalable Long-Horizon Planning with Staggered Updates for Lifelong MAPF
• WinkTPG: An Execution Framework for Multi-Agent Path Finding Using Temporal Reasoning
• MAPF-World: Action World Model for Multi-Agent Path Finding
• Planning over MAPF Agent Dependencies via Multi-Dependency PIBT
• A Theoretical Framework for Parallel Lifelong MAPF Using Group Decentralized Planning

Source: arXiv cs.AI | 2026-10-28