AI RESEARCH
End-to-end PDDL Planning with Hardcoded and Dynamic Agents
arXiv CS.AI
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ArXi:2512.09629v2 Announce Type: replace We present an end-to-end framework for planning ed by verifiers. An orchestrator receives a human specification written in natural language and converts it into a PDDL (Planning Domain Definition Language) model, where the domain and problem are iteratively refined by sub-modules (agents) to address common planning requirements, such as time constraints and optimality, as well as ambiguities and contradictions that may exist in the human specification.