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Dr. Sanjeev Namjoshi - Active Inference

Machine Learning Street Talk (MLST)

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Exploring Active Inference and Cognitive Modeling

This chapter examines the interplay between dynamic states in active inference using geometric visualizations, emphasizing action and exploration for reducing surprise and enhancing understanding of environments. It contrasts continuous and discrete state space models, discussing advancements in their applications and their relevance in cognitive processes. The conversation further explores decision-making complexities, cognitive load, and the role of biological imperatives in fostering exploration as a means to maintain equilibrium and minimize uncertainty.

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