06ME846-Artificial Intelligence |
PART – A |
UNIT I: |
ARTIFICIAL INTELLIGENCE: Introduction, definition, underlying
assumption, importance f A1, AI and related fields.
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UNIT II: |
SPACE REPRESENTATION: Defining a problem. Production systems
and its characteristics, Search and Control strategies – Generate and Test,
Hill Climbing, Best – first Search, Problem reduction, ConstraintSatisfaction, Means – Ends Analysis
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UNIT III: |
KNOWLEDGE REPRESENTATION ISSUES: Representations and
Mappings, Types of knowledge – Procedural Vs Declarative, Logic
programming. Forward Vs Backward reasoning, Matching.
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UNIT IV: |
USE OF PREDICATE LOGIC: Representing simple facts, Instance and Isa
relationships, Syntax and Semantics for Prepositional logic, FQPL and
properties of Wffs, Conversion to Clausal form, Resolution, Natural
deduction.
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PART – B |
UNIT V: |
STATISTICAL AND PROBABILISTIC REASONING: Symbolic
reasoning under uncertainty, Probability and Bayes’ theorem, Certainity
factors and Rule based systems, Bayesian Networks, Shafer Theory, Fuzzy
Logic.
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UNIT VI: |
EXPERT SYSTEMS: Structure and uses, Representing and using domain
knowledge, Expert System Shells. Pattern recognition Learning classification
patterns, recognizing and understanding speech. Introduction to knowledge
Acquisition, Types of Learning.
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UNIT VII: |
TYPICAL EXPERT SYSTEMS: MYCIN, Variants of MYCIN,
PROSPECTOR, DENDRAL, PUFF, ETC.
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UNIT VIII: |
INTRODUCTION TO MACHINE LEARNING: Perceptrons, Checker
Playing Examples, Learning Automata, Genetic Algorithms, Intelligent
Editors.
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REFERENCE |
TEXT BOOKS: |
1. Artificial Intelligence, Elaine Rich & Kevin Knight, M/H 1983.
2. Introduction to AI & ES, Dan W. Patterson, Prentice Hall of India,
1999.
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Reference Books |
1. Principles of Artificial Intelligence, Springer Verlag, Berlin, 1981.
2. Artificial Intelligence in business, Science & Industry, Wendy B.
Ranch
3. A guide to expert systems, Waterman, D.A., Addison – Wesley
inc. 1986
4. Building expert systems, Hayes, Roth, Waterman, D.A. Addison –
Wesley, 1983
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