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David B. Kinney on the Philosophy of Science

COMPLEXITY

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Causality and Probability in Scientific Models

This chapter explores the intricate relationship between causality and probability, emphasizing mathematical formalism and graph theory for modeling causal relationships. It discusses the complexities of defining probability, especially within the context of astrobiology, and examines the causal Markov condition's role in understanding information flow within systems. Additionally, the chapter delves into various methodologies, addressing the limitations of machine learning in capturing causal structures and the significance of granularity in scientific inquiry.

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