389 citations · 2.9k across the 113 of their papers we have counts for
36 papers · 1 filter
LLM-Guided Probabilistic Program Induction for POMDP Model Estimation
Aidan Curtis, Hao Tang, Thiago Veloso +4
Partially Observable Markov Decision Processes (POMDPs) model decision making under uncertainty. While there are many approaches to approximately solving POMDPs, we aim to address…
Generalized Planning in PDDL Domains with Pretrained Large Language Models
Tom Silver, Soham Dan, Kavitha Srinivas +3
Recent work has considered whether large language models (LLMs) can function as planners: given a task, generate a plan. We investigate whether LLMs can serve as generalized planne…
Learning Rational Subgoals from Demonstrations and Instructions
Zhezheng Luo, Jiayuan Mao, Jiajun Wu +3
We present a framework for learning useful subgoals that support efficient long-term planning to achieve novel goals. At the core of our framework is a collection of rational subgo…
PDSketch: Integrated Planning Domain Programming and Learning
Jiayuan Mao, Tomás Lozano-Pérez, Joshua B. Tenenbaum +1
This paper studies a model learning and online planning approach towards building flexible and general robots. Specifically, we investigate how to exploit the locality and sparsity…
Learning Efficient Abstract Planning Models that Choose What to Predict
Nishanth Kumar, Willie McClinton, Rohan Chitnis +3
An effective approach to solving long-horizon tasks in robotics domains with continuous state and action spaces is bilevel planning, wherein a high-level search over an abstraction…
PG3: Policy-Guided Planning for Generalized Policy Generation
Ryan Yang, Tom Silver, Aidan Curtis +2
A longstanding objective in classical planning is to synthesize policies that generalize across multiple problems from the same domain. In this work, we study generalized policy se…