AIBullisharXiv – CS AI · 9h ago7/10
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Learning and Reusing Policy Decompositions for Hierarchical Generalized Planning with LLM Agents
Researchers introduce HCL-GP, a machine learning approach that enables large language model agents to learn and reuse hierarchical task decompositions for improved performance on complex applications. The method achieves 98.2% accuracy on standard tasks and demonstrates significant improvements over static synthesis approaches, particularly benefiting open-source models through dynamic component reuse.