Towards An LLM-Driven Unified Conversion Framework for BT and FSM in Autonomous Intelligent Systems
Read the original on arXiv AI →The paper introduces an LLM-driven framework that automatically converts between finite state machines (FSM) and behavior trees (BT) for autonomous intelligent systems. It addresses key challenges such as preserving behavioral completeness and preventing model complexity explosion by designing a loop execution BT structure and employing depth compression strategies with LLM prompts. Experiments in various autonomous decision-making scenarios show that the framework achieves accurate, scalable, and maintainable bidirectional conversion, benefiting consumer-grade applications like service robots, game agents, and smart home devices.
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