
Dr. Thomas Parr - Active Inference Book
Machine Learning Street Talk (MLST)
Exploring Causality and Model Complexity
This chapter investigates the nuanced concept of causality, its definitions, and implications across predictive systems and physics. It emphasizes the significance of rigorous experimental designs and dynamic causal modeling while discussing the challenges of establishing true causal relationships. Additionally, it highlights the interconnectedness of various disciplines and advocates for a multidisciplinary approach to enhance collaboration and innovation.
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