AINeutralarXiv – CS AI · Mar 67/10
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BioLLMAgent: A Hybrid Framework with Enhanced Structural Interpretability for Simulating Human Decision-Making in Computational Psychiatry
Researchers introduce BioLLMAgent, a hybrid framework combining reinforcement learning models with large language models to simulate human decision-making in computational psychiatry. The framework demonstrates strong interpretability while accurately reproducing human behavioral patterns and successfully simulating cognitive behavioral therapy principles.