arXiv:2606. 14574v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as planners for autonomous agents in household environments.
By Xiaoxin Lu, Ranran Haoran Zhang, Rui Zhang
arXiv:2606. 27757v1 Announce Type: new Abstract: Large language models (LLMs) have attracted widespread attention from academia and industry, yet their deployment raises critical security concerns regarding robustness and reliability.
By Jiajing Zhang, Jiamei Jiang, Chenyang Zhang, Feifei Mo, Linjing Li, Daniel Zeng
arXiv:2606. 10489v1 Announce Type: new Abstract: Automated Planning is a subfield of Artificial Intelligence (AI) where the main objective is generating a sequence of actions, known as a plan, that helps us reach a goal state from an initial state.
By Youssef Abdelkader, Humbert Fiorino, Damien Pellier
arXiv:2607. 21414v1 Announce Type: new Abstract: In automated planning, logical regression is an operation that returns the most general condition necessary for an action to achieve a particular formula.
By Connor Little, Christian Muise
arXiv:2505. 13372v2 Announce Type: replace Abstract: Recent work investigated the use of Reinforcement Learning (RL) for the synthesis of heuristic guidance to improve the performance of temporal planners when a domain is fixed and a set of training problems (not plans) is given.
By Irene Brugnara, Alessandro Valentini, Andrea Micheli
arXiv:2510. 00182v2 Announce Type: replace-cross Abstract: While we know that large language models (LLMs) can solve some planning problems, we do not understand the extent of these capabilities for robotics.
By Jorge Mendez-Mendez