Reward Framework Debate
Tim and Minqi discuss the concept of using rewards as a basis for intelligent agent behavior. Minqi highlights challenges in defining reward functions despite the theoretical framework's potential. They explore the integration of rewards into world models for deriving desired behavior.In this clip
From this podcast
Machine Learning Street Talk (MLST)
Can we build a generalist agent? Dr. Minqi Jiang and Dr. Marc Rigter
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