4 citations · 7 across the 10 of their papers we have counts for
6 papers · 1 filter
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…
Large Language Models as Planning Domain Generators
James Oswald, Kavitha Srinivas, Harsha Kokel +3
Developing domain models is one of the few remaining places that require manual human labor in AI planning. Thus, in order to make planning more accessible, it is desirable to auto…
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…