Reasoning with probabilistic and deterministic graphical models
by Rina Dechter
Graphical modeling (Statistics)Bayesian statistical decision theoryReasoningAlgorithmsMachine learning
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Open LibraryAbout this book
Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reasoning tasks, such as scheduling, planning and learning, diagnosis and prediction, design, hardware and software verification, and bioinformatics. These problems can be stated as the formal tasks of constraint satisfaction and satisfiability, combinatorial optimization, and probabilistic inference.
Themes & subjects
Graphical modeling (Statistics)Bayesian statistical decision theoryReasoningAlgorithmsMachine learningCOMPUTERS
About the author
Rina Dechter
1950
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