Natural Language PDDL (NL-PDDL) for Open-world Goal-oriented Commonsense Regression Planning in Embodied AI
Published in ICLR 2026 (Poster), 2026
A neurosymbolic agentic planning framework that enforces sound and deterministic reasoning for LLM-based agents in open-world environments, improving previous baselines by 373% and attaining state-of-the-art across central benchmarks.
Recommended citation: Xiaotian Liu, Armin Toroghi, Jiazhou Liang, David Courtis, Ruiwen Li, Ali Pesaranghader, Jaehong Kim, Tanmana Sadhu, Hyejeong Jeon, Scott Sanner. (2026). "Natural Language PDDL (NL-PDDL) for Open-world Goal-oriented Commonsense Regression Planning in Embodied AI." International Conference on Learning Representations (ICLR).
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