Academics / Courses / Course DescriptionsMECH_ENG 495: Physical Intelligence and Embodied AI
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Prerequisites
Prerequisites: dynamics; programming (Python or equivalent); some exposure to feedback control recommended.Description
Recent advances in artificial intelligence have been driven primarily by large-scale learning from static datasets. However, biological intelligence emerges through continuous interaction among brains, bodies, and environments. This course develops physical intelligence—the idea that morphology, mechanics, and the sensorimotor loop perform real computation—and connects it to modern embodied AI, where agents that act in physical or simulated environments learn very differently from disembodied ones. Building on the mechanics, dynamics, controls, and programming background of mechanical engineering students, the course moves from “brainless” mechanical intelligence (passive-dynamic walkers, compliant bodies) through active sensing and feedback to reinforcement learning, planning, and the evolutionary origins of cognition. Students implement embodied agents in simulation and build a final agent that senses, acts, and learns in a predator–prey arena modeled on the instructor’s research.
Course Outline