4 citations · 7 across the 10 of their papers we have counts for
9 papers · 1 filter
Planning in the LLM Era: Building for Reliability and Efficiency
Michael Katz, Harsha Kokel, Kavitha Srinivas +1
Growing attention to intelligent agents has put a spotlight on one of their central capabilities: planning. Early attempts to leverage large language models (LLMs) for planning rel…
Learning and Reusing Policy Decompositions for Hierarchical Generalized Planning with LLM Agents
Shirin Sohrabi, Haritha Ananthakrishnan, Harsha Kokel +2
We present a dynamic policy-learning approach that combines generalized planning and hierarchical task decomposition for LLM-based agents. Our method, Hierarchical Component Learni…
Model Space Reasoning as Search in Feedback Space for Planning Domain Generation
James Oswald, Daniel Obolensky, Volodymyr Varha +5
The generation of planning domains from natural language descriptions remains an open problem even with the advent of large language models and reasoning models. Recent work sugges…
ACPBench Hard: Unrestrained Reasoning about Action, Change, and Planning
Harsha Kokel, Michael Katz, Kavitha Srinivas +1
The ACPBench dataset provides atomic reasoning tasks required for efficient planning. The dataset is aimed at distilling the complex plan generation task into separate atomic reaso…
ACPBench: Reasoning about Action, Change, and Planning
Harsha Kokel, Michael Katz, Kavitha Srinivas +1
There is an increasing body of work using Large Language Models (LLMs) as agents for orchestrating workflows and making decisions in domains that require planning and multi-step re…
Automating Thought of Search: A Journey Towards Soundness and Completeness
Daniel Cao, Michael Katz, Harsha Kokel +2
Large language models (LLMs) are being used to solve planning problems that require search. Most of the literature uses LLMs as world models to define the search space, forgoing so…
Thought of Search: Planning with Language Models Through The Lens of Efficiency
Michael Katz, Harsha Kokel, Kavitha Srinivas +1
Among the most important properties of algorithms investigated in computer science are soundness, completeness, and complexity. These properties, however, are rarely analyzed for t…
Some Orders Are Important: Partially Preserving Orders in Top-Quality Planning
Michael Katz, Junkyu Lee, Jungkoo Kang +1
The ability to generate multiple plans is central to using planning in real-life applications. Top-quality planners generate sets of such top-cost plans, allowing flexibility in de…
Unifying and Certifying Top-Quality Planning
Michael Katz, Junkyu Lee, Shirin Sohrabi
The growing utilization of planning tools in practical scenarios has sparked an interest in generating multiple high-quality plans. Consequently, a range of computational problems…