Cambridge Studies in Probability, Induction and Decision Theory Reeks

How can we identify events due to intelligent causes and distinguish them from events due to undirected natural causes? If we lack a causal theory how can we determine whether an intelligent cause acted? This book presents a reliable method for detecting intelligent causes: the design inference. The design inference uncovers intelligent causes by isolating the key trademark of intelligent causes: specified events of small probability. Design inferences can be found in a range of scientific pursuits from forensic science to research into the origins of life to the search for extraterrestrial intelligence. This challenging and provocative book will be read with particular interest by philosophers of science and religion, other philosophers concerned with epistemology and logic, probability and complexity theorists, and statisticians.

Multidimensional utility analysis enhances decision theory by integrating traditional and innovative evaluation methods into a cohesive framework. It formulates key decision principles like maximizing expected utility and addresses complex decision-making scenarios, particularly when an expert represents a group. This comprehensive approach accommodates various factors influencing an option's utility, making it a crucial resource for advanced students, professionals in decision theory, and social scientists.

This book offers an in-depth exploration of causal asymmetry, presenting a thorough analysis from a leading philosopher of science. It delves into the complexities of cause and effect relationships, examining their implications across various scientific disciplines. The author provides critical insights and arguments, making it an essential resource for those interested in the philosophical underpinnings of causation and its impact on scientific understanding.