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Open tools for automated planning — CUDA-accelerated and classical planners,
multi-agent pathfinding, and PDDL tooling.
Everything here is an implementation of published work, written to be read as
well as run. Each README says what the tool does and what it does not do; if
one doesn't, that is a bug worth filing.
The same algorithms batched onto a GPU, with a NumPy reference backend. Installs as cuplan — the repository and the distribution are deliberately named differently.
Grid maps, search animations, plan timelines and benchmark charts, light and dark from the same call. Planners not included — it draws results, it does not produce them. On PyPI.
Bug reports and PDDL instances are the easiest ways in; both have
templates.
The contributing guide
covers the PR flow, and each project's own README covers its specifics.
Security reports go privately to the address in the
security policy.
A Python library for multi-agent planning and pathfinding: CBS, PIBT, LaCAM, LNS, space-time A*, plus decentralized NMPC, velocity obstacles and swarm behaviors
Reproducible benchmarking harness and living leaderboard for the OpenPlan Labs planners — classical PDDL and MAPF, with timeouts and errors recorded as results
Reproducible benchmarking harness and living leaderboard for the OpenPlan Labs planners — classical PDDL and MAPF, with timeouts and errors recorded as results
A Python library for multi-agent planning and pathfinding: CBS, PIBT, LaCAM, LNS, space-time A*, plus decentralized NMPC, velocity obstacles and swarm behaviors