GenePlan: Evolving Better Generalized PDDL Plans using Large Language Models
We present GenePlan (GENeralized Evolutionary Planner), a novel framework that leverages large language model (LLM) assisted evolutionary algorithms to generate domain-dependent generalized planners for classical planning tasks described in PDDL. By casting generalized planning as an optimization problem, GenePlan iteratively evolves interpretable Python planners that minimize plan length across diverse problem instances. In empirical evaluation across six existing benchmark domains and two new domains, GenePlan achieved an average SAT score of 0.91, closely matching the performance of the state-of-the-art planners (SAT score 0.93), and significantly outperforming other LLM-based baseline...
| Authors | Andrew Murray, Danial Dervovic, Alberto Pozanco et al. |
|---|---|
| Primary category | cs.AI |
| Published | 10 March 2026 |
| Last updated at source | 10 March 2026 |
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