Free Reasoning about Uncertainty (MIT Press)
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In order to deal with uncertainty intelligently, we need to be able to represent it and reason about it. In this book, Joseph Halpern examines formal ways of representing uncertainty and considers various logics for reasoning about it. While the ideas presented are formalized in terms of definitions and theorems, the emphasis is on the philosophy of representing and reasoning about uncertainty. Halpern surveys possible formal systems for representing uncertainty, including probability measures, possibility measures, and plausibility measures; considers the updating of beliefs based on changing information and the relation to Bayes' theorem; and discusses qualitative, quantitative, and plausibilistic Bayesian networks.This second edition has been updated to reflect Halpern's recent research. New material includes a consideration of weighted probability measures and how they can be used in decision making; analyses of the Doomsday argument and the Sleeping Beauty problem; modeling games with imperfect recall using the runs-and-systems approach; a discussion of complexity-theoretic considerations; the application of first-order conditional logic to security. Reasoning about Uncertainty is accessible and relevant to researchers and students in many fields, including computer science, artificial intelligence, economics (particularly game theory), mathematics, philosophy, and statistics. RACGP - Clinical reasoning - A guide to improving teaching The process of clinical reasoning is undertaken by all clinicians often automatically and is the cognitive process that underlies diagnosis and management of a Uncertainty - Wikipedia Uncertainty is a situation which involves imperfect and/or unknown information However "uncertainty is an unintelligible expression without a straightforward JUDEA PEARL'S HOMEPAGE - University of California Los Angeles Welcome to my homepage To find out what I am up to new submissions working papers adventures and introspections click here Textbook: Introduction to Probability 2nd Edition An intuitive yet precise introduction to probability theory stochastic processes statistical inference and probabilistic models used in science engineering Inference - Wikipedia AI systems first provided automated logical inference and these were once extremely popular research topics leading to industrial applications under the form of Computer Science and Intelligent Systems The MIT Press Proof is the primary vehicle for knowledge generation in mathematics In computer science proof has found an additional use: verifying that a particular system (or Readings - MIT OpenCourseWare About MIT OpenCourseWare MIT OpenCourseWare makes the materials used in the teaching of almost all of MIT's subjects available on the Web free of charge The social power of algorithms: Information Communication ABSTRACTThis article explores the questions associated with what might be thought of as the social power of algorithms The article which introduces a special issue Money: The Brave New Uncertainty of Mervyn King by Paul The Bank of England founded in 1694 isnt the oldest central bank in the world an honor that belongs to Swedens Riksbank founded a quarter-century earlier Tools for Decision Analysis - ubaltedu Decision Analysis: Making Justifiable Defensible Decisions Decision analysis is the discipline of evaluating complex alternatives in terms of values and uncertainty
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