Author

Jörg Hoffmann

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#artificial intelligence Preprint Sep 2026

Provably Complete Generalized Planning with LLMs

This work introduces a semantic-preserving PDDL-to-Lean conversion, and uses an LLM to generate both the generalized plan and the formal proof that it solves every instance satisfying the domain constraints, and evaluates this approach on 13 commonly used benchmark domains.

Katharina Stein, Chaahat Jain, J. Hoffmann et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Generating Instance Generators in PDDL Planning

This work leveraging LLMs to generate instance-generation programs, with built-in soundness guarantees through prescribed checks, and shows that these automatically generated instance generators return large numbers of sound and diverse instances efficiently.

Nicola J. Müller, Naya Rudolph, Katharina Stein et al. · 0 citations