An agentic LLM framework augmented with symbolic feedback and heuristic search over model space generates improved planning domains from natural language descriptions.
ISR-LLM: iterative self- refined large language model for long-horizon sequential task planning
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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.