Classical logic forms the basis of knowledge representation and reasoning in AI. In the real world, however, classical logic alone is insufficient to describe the reasoning behaviour of human beings. It lacks the flexibility so characteristically required of reasoning under uncertainty, reasoning under ...
plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic ...
ReasoningUnderUncertainty;ApplicationsofMachine LearningandAI. EDUCATIONUniversityofMassachusetts,Amherst Ph.D.inComputerScienceExpected:May2000 Advisor:Dr.RichardS.Sutton UniversityofMassachusetts,Amherst M.Sc.inComputerScience,GPA4.0/4.0February1996 TechnicalUniversityCluj-Napoca,Romania AdvancedStudies(M.S.)in...
Textbook offers an accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. For graduate-level courses in AI, operations research, and applied probability. Annotation copyrighted by Book News, Inc., Portland, OR 关键词: Artificial inte...
account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as.....
Reasoning under uncertainty with limited resources and incomplete knowledge plays a big role in everyday situations and also in many technical applications of AI. Probabilistic reasoning is the modern AI method for solving these problems. After a brief introduction to probability theory we present the...
annually since 1996. The UR 2025 Special Track at the 38th International Florida Artificial Intelligence Research Society Conference (FLAIRS-38) is the 30th in the series. Like the past tracks, UR'25 seeks to bring together researchers working on broad issues related to reasoning under uncertainty...
AI - Knowledge-Based Agent Levels AI - Backus-Naur Form (BNF) AI - Uncertainty AI - Reasons for Uncertainty AI - Probabilistic Reasoning AI - Conditional Probability AI - Bayes Theorem AI - Certainty Factor AI - Inference in Terms AI - Decision Making Under Uncertainty ...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers...
UNCERTAINTY IN AI SYSTEMS JudeaPearl, inProbabilistic Reasoning in Intelligent Systems, 1988 THE ROLE OF BIDIRECTIONAL INFERENCES The ability to use both predictive anddiagnostic informationis an important component of plausible reasoning, and improper handling of such information leads to rather strange re...