Rich, Knight, Nair: Artificial intelligence, Tata McGraw Hill, Third Edition 2009. Russell, Norvig, Artificial intelligence, A Modern Approach, Pearson Education, Second Edition. UNIT-V Advanced Knowledge Representation Techniques: Case Grammars, Semantic Web Natural Language Processing: Introduction, Sentence Analysis Phases, Grammars and Parsers, Types of Parsers, Semantic Analysis, Universal Networking Knowledge. With effect from the Academic Year 2012-2013 The book has been w ritten keeping in mind the syllabi designed for courses on AI in various technical institutions and universities in India and abroad. Artificial Neural Networks: Introduction, Artificial Neural Networks, Single-Layer FeedForward Networks, Multi-Layer Feed-Forward Networks, Radial- Basis Function Networks, Design Issues of Artificial Neural Networks, Recurrent Networks. This textbook Artificial Intelligence is designed to provide comprehensive material to undergraduate and graduate students on the vast and fast-grow ing subject of Artificial Intelligence. 2) S Kaushik, Artificial Intelligence, Cengage Learning. Learning Decision Trees (Suggested Reading 2), Deductive Learning. 1) Introduction to Artificial Intelligence & Expert Systems, Dan W Patterson, PHI.,2010. UNIT-IV Machine-Learning Paradigms: Introduction. Uncertainty Measure - Probability Theory: Introduction, Probability Theory, Bayesian Belief Networks, Certainty Factor Theory, Dempster-Shafer Theory. Introduction to Artificial Intelligence Lecture Module 1 Prof Saroj Kaushik 1 Contents. 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. View L1 from CSE 07 at Andhra University. 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. Artificial Intelligence Artificial Intelligence- Saroj Kaushik, CENGAGE Learning, The Artificial intelligence, A Modern Approach, 2nd ed, Stuart Russel. 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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