10 citations · 11 across the 5 of their papers we have counts for
5 papers
ProRAC: A Neuro-symbolic Method for Reasoning about Actions with LLM-based Progression
Haoyong Wu, Yongmei Liu
In this paper, we propose ProRAC (Progression-based Reasoning about Actions and Change), a neuro-symbolic framework that leverages LLMs to tackle RAC problems. ProRAC extracts fund…
Planning with Dynamically Changing Domains
Mikhail Soutchanski, Yongmei Liu
In classical planning and conformant planning, it is assumed that there are finitely many named objects given in advance, and only they can participate in actions and in fluents. T…
TRAC: A Textual Benchmark for Reasoning about Actions and Change
Weinan He, Canming Huang, Zhanhao Xiao +1
Reasoning about actions and change (RAC) is essential to understand and interact with the ever-changing environment. Previous AI research has shown the importance of fundamental an…
Automatic Verification of Sound Abstractions for Generalized Planning
Zhenhe Cui, Weidu Kuang, Yongmei Liu
Generalized planning studies the computation of general solutions for a set of planning problems. Computing general solutions with correctness guarantee has long been a key issue i…
A General Multi-agent Epistemic Planner Based on Higher-order Belief Change
Xiao Huang, Biqing Fang, Hai Wan +1
In recent years, multi-agent epistemic planning has received attention from both dynamic logic and planning communities. Existing implementations of multi-agent epistemic planning…