Computing Non-Causal Knowledge for Causal Reasoning
MCMP – Mathematical Philosophy (Archive 2011/12)
English - June 28, 2011 00:00 - 55 minutes - 524 MB Video - ★★★★★ - 6 ratingsPhilosophy Society & Culture philosophy logic science language mathematics hannes leitgeb stephan hartmann mcmp lmu Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
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Roland Poellinger (MCMP/LMU Munich) gives a talk at the MCMP Workshop on Computational Metaphysics titled "Computing Non-Causal Knowledge for Causal Reasoning". Abstract: We use logical and mathematical knowledge to generate causal claims. Inter-definitions or semantic overlap cannot be consistently embedded in standard Bayes net causal models since in many cases the Markov requirement will be violated. These considerations motivate an extension of Bayes net causal models to also allow for the embedding of Epistemic Contours (ECs). Such non-causal functions are consistently computable in Causal Knowledge Patterns (CKPs). An application of the framework can be found, e.g., in the recording of the talk "The Mind-Brain Entanglement".