On the prospects of incorporating large language models (llms) in automated planning and scheduling (aps)

V Pallagani, BC Muppasani, K Roy, F Fabiano… - Proceedings of the …, 2024 - ojs.aaai.org
Abstract Automated Planning and Scheduling is among the growing areas in Artificial
Intelligence (AI) where mention of LLMs has gained popularity. Based on a comprehensive …

Safety-critical advanced robots: A survey

J Guiochet, M Machin, H Waeselynck - Robotics and Autonomous Systems, 2017 - Elsevier
Develo** advanced robotics applications is now facing the safety issue for users, the
environment, and the robot itself, which is a main limitation for their deployment in real life …

On the planning abilities of large language models-a critical investigation

K Valmeekam, M Marquez… - Advances in …, 2023 - proceedings.neurips.cc
Intrigued by the claims of emergent reasoning capabilities in LLMs trained on general web
corpora, in this paper, we set out to investigate their planning capabilities. We aim to …

Leveraging pre-trained large language models to construct and utilize world models for model-based task planning

L Guan, K Valmeekam, S Sreedharan… - Advances in …, 2023 - proceedings.neurips.cc
There is a growing interest in applying pre-trained large language models (LLMs) to
planning problems. However, methods that use LLMs directly as planners are currently …

Position: LLMs can't plan, but can help planning in LLM-modulo frameworks

S Kambhampati, K Valmeekam, L Guan… - … on Machine Learning, 2024 - openreview.net
We argue that auto-regressive LLMs cannot, by themselves, do planning or self-verification
(which is after all a form of reasoning), and shed some light on the reasons for …

Large language models still can't plan (a benchmark for LLMs on planning and reasoning about change)

K Valmeekam, A Olmo, S Sreedharan… - … Models for Decision …, 2022 - openreview.net
Recent advances in large language models (LLMs) have transformed the field of natural
language processing (NLP). From GPT-3 to PaLM, the state-of-the-art performance on …

Generalized planning in pddl domains with pretrained large language models

T Silver, S Dan, K Srinivas, JB Tenenbaum… - Proceedings of the …, 2024 - ojs.aaai.org
Recent work has considered whether large language models (LLMs) can function as
planners: given a task, generate a plan. We investigate whether LLMs can serve as …

Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change

K Valmeekam, M Marquez, A Olmo… - Advances in …, 2023 - proceedings.neurips.cc
Generating plans of action, and reasoning about change have long been considered a core
competence of intelligent agents. It is thus no surprise that evaluating the planning and …

Can large language models really improve by self-critiquing their own plans?

K Valmeekam, M Marquez, S Kambhampati - arxiv preprint arxiv …, 2023 - arxiv.org
There have been widespread claims about Large Language Models (LLMs) being able to
successfully verify or self-critique their candidate solutions in reasoning problems in an …

[PDF][PDF] On the planning abilities of large language models (a critical investigation with a proposed benchmark)

K Valmeekam, S Sreedharan, M Marquez… - arxiv preprint arxiv …, 2023 - researchgate.net
Intrigued by the claims of emergent reasoning capabilities in LLMs trained on general web
corpora, in this paper, we set out to investigate their planning capabilities. We aim to …