Future State Learning
Tim and Bert delve into the concept of future state learning, contrasting it with traditional reinforcement learning. They discuss the importance of setting constraints on generative models to shape desired future states, emphasizing resource conservation and smart data utilization in active inference processes.In this clip
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Machine Learning Street Talk (MLST)
Prof. BERT DE VRIES - ON ACTIVE INFERENCE
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