Bayesian programming. (2013)

• Record Type: Book
• Further Information: Note: Pierre Bessiere, Emmanuel Mazer, Juan Manuel Ahuactzin, Kamel Mekhnacha.
• Authors: Bessière, Pierre; Mazer, Emmanuel; Ahuactzin, Juan-Manuel; Mekhnacha, Kamel
• Contents: Introduction; Probability an alternative to logic; A need for a new computing paradigm; A need for a new modeling methodology; A need for new inference algorithms; A need for a new programming language and new hardware; A place for numerous controversies; Running real programs as exercises Bayesian Programming Principles ; Basic Concepts; Variable; Probability; The normalization postulate; Conditional probability; Variable conjunction; The conjunction postulate (Bayes theorem); Syllogisms; The marginalization rule; Joint distribution and questions; Decomposition; Parametric forms; Identification; Specification = variables + decomposition + parametric forms; Description = specification + identification; Question; Bayesian program = description + question; Results Incompleteness and Uncertainty ; Observing a water treatment unit; Lessons, comments, and notes Description = Specification + Identification ; Pushing objects and following contours; Description of a water treatment unit; Lessons, comments, and notes The Importance of Conditional Independence ; Water treatment center Bayesian model (continuation); Description of the water treatment center; Lessons, comments, and notes Bayesian Program = Description + Question ; Water treatment center Bayesian model (end); Forward simulation of a single unit; Forward simulation of the water treatment center; Control of the water treatment center; Diagnosis; Lessons, comments, and notes Bayesian Programming Cookbook; Information Fusion; "Naive" Bayes sensor fusion; Relaxing the conditional independence fundamental hypothesis; Classification; Ancillary clues; Sensor fusion with false alarm; Inverse programming Bayesian Programming with Coherence Variables; Basic example with Boolean variables; Basic example with discrete variables; Checking the semantic of Λ; Information fusion revisited using coherence variables; Reasoning with soft evidence; Switch; Cycles Bayesian Programming Subroutines ; The sprinkler model; Calling subroutines conditioned by values; Water treatment center revisited (final); Fusion of subroutines; Superposition Bayesian Programming Conditional Statement ; Bayesian if-then-else; Behavior recognition; Mixture of models and model recognition Bayesian Programming Iteration ; Generic iteration; Generic Bayesian filters; Markov localization Bayesian Programming Formalism and Algorithms; Bayesian Programming Formalism ; Logical propositions; Probability of a proposition; Normalization and conjunction postulates; Disjunction rule for propositions; Discrete variables; Variable conjunction; Probability on variables; Conjunction rule for variables; Normalization rule for variables; Marginalization rule; Bayesian program; Description; Specification; Questions; Inference Bayesian Models Revisited ; General purpose probabilistic models; Engineering-oriented probabilistic models; Cognitive-oriented probabilistic models Bayesian Inference Algorithms Revisited ; Stating the problem; Symbolic computation; Numerical computation: General sampling algorithms for approximate Bayesian inference; Approximate inference in ProBT Bayesian Learning Revisited; Parameter identification; Expectation-Maximization (EM); Learning structure of Bayesian networks Frequently Asked Questions and Frequently Argued Matter ; Frequently Asked Question and Frequently Argued Matter; Alternative Bayesian inference engines; Bayesian programming applications; Bayesian programming vs. Bayesian networks; Bayesian programming vs. Bayesian modeling; Bayesian programming vs. possibility theories; Bayesian programming vs. probabilistic programming; Computational complexity of Bayesian inference; Cox theorem; Discrete vs. continuous variables; Incompleteness irreducibility; Maximum entropy principle justifications; Noise or ignorance?; Objectivism vs. subjectivism controversy and the "mind projection fallacy"; Unknown distribution Glossary; Bayesian filter; Bayesian inference; Bayesian network; Bayesian program; Coherence variable; Conditional statement; Decomposition; Description; Forms; Incompleteness; Mixture; Noise; Preliminary knowledge; Question; Specification; Subroutines; Variable Index
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2013
• Extent: 1 online resource, illustrations
• Subjects: 005.101519542; Computer science -- Mathematics; Bayesian statistical decision theory -- Data processing
• Languages: English
• ISBNs: 9781439880333
• Notes: Note: Description based on CIP data; resource not viewed.
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