An agentic LLM framework augmented with symbolic feedback and heuristic search over model space generates improved planning domains from natural language descriptions.
Text2world: Benchmarking large language models for sym- bolic world model generation
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Model Space Reasoning as Search in Feedback Space for Planning Domain Generation
An agentic LLM framework augmented with symbolic feedback and heuristic search over model space generates improved planning domains from natural language descriptions.