18 citations · 27 across the 15 of their papers we have counts for
16 papers
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…
QueryGym: Step-by-Step Interaction with Relational Databases
Haritha Ananthakrishnan, Harsha Kokel, Kelsey Sikes +4
We introduce QueryGym, an interactive environment for building, testing, and evaluating LLM-based query planning agents. Existing frameworks often tie agents to specific query lang…
Make Planning Research Rigorous Again!
Michael Katz, Harsha Kokel, Christian Muise +2
In over sixty years since its inception, the field of planning has made significant contributions to both the theory and practice of building planning software that can solve a nev…
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…