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cs.AI2026
Iterative Formalization and Planning in Partially Observable Environments
Liancheng Gong, Wang Zhu, Jesse Thomason +1
Using LLMs not to predict plans but to formalize an environment into the Planning Domain Definition Language (PDDL) has been shown to improve performance and control. While most ex…
cs.AI2025
TwoStep: Multi-agent Task Planning using Classical Planners and Large Language Models
David Bai, Ishika Singh, David Traum +1
Classical planning formulations like the Planning Domain Definition Language (PDDL) admit action sequences guaranteed to achieve a goal state given an initial state if any are poss…
cs.AI2024
Language Models can Infer Action Semantics for Symbolic Planners from Environment Feedback
Wang Zhu, Ishika Singh, Robin Jia +1
Symbolic planners can discover a sequence of actions from initial to goal states given expert-defined, domain-specific logical action semantics. Large Language Models (LLMs) can di…