5 papers
Provably Complete Generalized Planning with LLMs
Katharina Stein, Chaahat Jain, Jörg Hoffmann +1
Generalized planning aims to compute a plan that solves all instances of a planning domain. Recent work has used LLMs to automatically generate and debug such generalized plans in…
Generating Instance Generators in PDDL Planning
Nicola J. Müller, Naya Rudolph, Katharina Stein +3
PDDL, the de-facto standard language in the AI Planning community, is designed to specify planning domains: sets of instances that share the same predicates and action schemas. Yet…
On the Ability of Transformers to Verify Plans
Yash Sarrof, Yupei Du, Katharina Stein +3
Transformers have shown inconsistent success in AI planning tasks, and theoretical understanding of when generalization should be expected has been limited. We take important steps…
Improved Generalized Planning with LLMs through Strategy Refinement and Reflection
Katharina Stein, Nils Hodel, Daniel Fišer +3
LLMs have recently been used to generate Python programs representing generalized plans in PDDL planning, i.e., plans that generalize across the tasks of a given PDDL domain. Previ…
Automating the Generation of Prompts for LLM-based Action Choice in PDDL Planning
Katharina Stein, Daniel Fišer, Jörg Hoffmann +1
Large language models (LLMs) have revolutionized a large variety of NLP tasks. An active debate is to what extent they can do reasoning and planning. Prior work has assessed the la…