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Learning Decision Trees (Suggested Reading 2), Deductive Learning. UNIT-IV Machine-Learning Paradigms: Introduction. Uncertainty Measure - Probability Theory: Introduction, Probability Theory, Bayesian Belief Networks, Certainty Factor Theory, Dempster-Shafer Theory. UNIT-III Expert System and Applications: Introduction, Phases in Building Expert Systems, Expert System Architecture, Expert Systems vs Traditional Systems, Truth Maintenance Systems, Application of Expert Systems, List of Shells and Tools. Knowledge Representation: Introduction, Approaches to Knowledge Representation, Knowledge Representation using Semantic Network, Extended Semantic Networks for KR, Knowledge Representation using Frames. Proble m Solving - State-Space Search and Control Strategies: Introduction, General Problem Solving, Characteristics of Problem, Exhaustive Searches, Heuristic Search Techniques, Iterative-Deepening A*, Constraint Satisfaction Game Playing: Bounded Look-ahead Strategy and use of Evaluation Functions, Alpha-Beta Pruning UNIT-II Logic Concepts and Logic Programming: Introduction, Propositional Calculus, Propositional Logic, Natural Deduction System, Axiomatic System, Semantic Tableau System in Propositional Logic, Resolution Refutation in Propositional Logic, Predicate Logic, Logic Programming. UNIT-I Introduction: History, Intelligent Systems, Foundations of AI, Sub areas of AI, Applications. With effect from the Academic Year 2012-2013 BIT 354ĪRTIFICIAL INTELLIGENCE Instruction Duration University Examination SessionalĤ Periods per week 3 Hours 75 Marks 25 Marks
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