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Topic: Active Inference

Active Inference is a unifying mathematical framework that models living systems as agents which minimize surprise and free energy in order to resist entropy and persist over time.

More on: Active Inference

The podcast episodes provided discuss the concept of Active Inference, which is a framework for building intelligent autonomous agents based on the free energy principle.

The episodes explore the high-level conceptual and low-level mathematical aspects of Active Inference, highlighting its unifying nature across various fields and its implications for understanding agency, biology, causality, modeling, and consciousness.

For example, the episode Dr. Thomas Parr - Active Inference Book features an interview with the co-author of a book on Active Inference, while the episode Prof. BERT DE VRIES - ON ACTIVE INFERENCE discusses the challenges in implementing Active Inference and its potential impact on software engineering and automated system design.

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