48 citations · 74 across the 9 of their papers we have counts for
10 papers
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…
A Conflict-driven Interface between Symbolic Planning and Nonlinear Constraint Solving
Joaquim Ortiz-Haro, Erez Karpas, Michael Katz +1
Robotic planning in real-world scenarios typically requires joint optimization of logic and continuous variables. A core challenge to combine the strengths of logic planners and co…
Reinforced Meta Active Learning
Michael Katz, Eli Kravchik
In stream-based active learning, the learning procedure typically has access to a stream of unlabeled data instances and must decide for each instance whether to label it and use i…
Hierarchical Reinforcement Learning with AI Planning Models
Junkyu Lee, Michael Katz, Don Joven Agravante +4
Two common approaches to sequential decision-making are AI planning (AIP) and reinforcement learning (RL). Each has strengths and weaknesses. AIP is interpretable, easy to integrat…
Efficient Meta Subspace Optimization
Yoni Choukroun, Michael Katz
Subspace optimization methods have the attractive property of reducing large-scale optimization problems to a sequence of low-dimensional subspace optimization problems. However, e…
Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generators
Clement Gehring, Masataro Asai, Rohan Chitnis +4
Recent advances in reinforcement learning (RL) have led to a growing interest in applying RL to classical planning domains or applying classical planning methods to some complex RL…