Thomas Berrueta led the development of Maximum Diffusion Reinforcement Learning (MaxDiff RL), a specific algorithm for robots, potentially transforming embodied AI in real-world applications.
Most existing reinforcement-learning algorithms assume independent and identically distributed data, challenging when applied to robots. MaxDiff RL tackles this limitation, enhancing learning capabilities for robots.
Challenges arise when reinforcement-learning algorithms designed for virtual systems encounter related and dependent data in real-world robotics scenarios.
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