AI RESEARCH
Agentic LLM Planning via Step-Wise PDDL Simulation: An Empirical Characterisation
arXiv CS.AI
•
ArXi:2603.06064v1 Announce Type: new Task planning, the problem of sequencing actions to reach a goal from an initial state, is a core capability requirement for autonomous robotic systems. Whether large language models (LLMs) can serve as viable planners alongside classical symbolic methods remains an open question. We present PyPDDLEngine, an open-source Planning Domain Definition Language (PDDL) simulation engine that exposes planning operations as LLM tool calls through a Model Context Protocol (MCP) interface.