Emotion in an active inference model of human driving
Researchers apply active inference to map human-like emotional states within complex, continuous driving environments.
Active inference has emerged as a principled framework for modeling adaptive behavior by balancing goal-directed action with uncertainty reduction. It has been successfully applied across biological and artificial systems, including recent work on human driving. However, existing...
ArXiv CS.AI
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Integrating emotional states into active inference driving models bridges the gap between purely rational decision-making and the nuanced, reactive nature of human behavior. By modeling valence and arousal within continuous traffic environments, researchers can develop more predictable and safer autonomous systems that better interpret or simulate human-like reactions.
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