Causality, probability, and time

Research output: Book/ReportBookpeer-review

57 Scopus citations

Abstract

Causality is a key part of many fields and facets of life, from finding the relationship between diet and disease to discovering the reason for a particular stock market crash. Despite centuries of work in philosophy and decades of computational research, automated inference and explanation remain an open problem. In particular, the timing and complexity of relationships have been largely ignored even though this information is critically important for prediction, explanation, and intervention. However, given the growing availability of large observational datasets, including those from electronic health records and social networks, it is a practical necessity. This book presents a new approach to inference (finding relationships from a set of data) and explanation (assessing why a particular event occurred), addressing both the timing and complexity of relationships. The practical use of the method developed is illustrated through theoretical and experimental case studies, demonstrating its feasibility and success.

Original languageEnglish
Number of pages259
Volume9781107026483
ISBN (Electronic)9781139207799
DOIs
StatePublished - 1 Jan 2009

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