Robust Asynchronous Planning via Auto-Formalization
LLMs can plan by generating schedules directly as a Planner, or by translating a task into a formal specification for a solver as a Formalizer. Most real-world tasks are asynchronous, with non-uniform durations, concurrency, and execution-time changes, yet existing benchmarks hardly cover them. We unify asynchronous planning under one formulation and release three benchmarks spanning task-graph scale, grounded state and resource constraints, and execution-time events. Surprisingly, PDDL2.1, the formalism built for temporal planning, is the weakest pipeline. On AsyncPlan-XXL it averages 30.8% plan accuracy, against 81.7% for the Planner and 94.0% for a CP-SAT Formalizer. The gap widens wit...
| Authors | Jiayi Zhang, Jianing Yin, Ben Zhou et al. |
|---|---|
| Primary category | cs.CL |
| Published | 31 May 2026 |
| Last updated at source | 14 October 2026 |
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