AI Problems, AI Techniques, The Level of the Model, Criteria or Success. Defining the Problem as a State Space Search, Problem Characteristics, Production Systems, Search: Issues in The Design of Search Programs, Un-Informed Search, BFS,DFS; Heuristic Search Techniques: Generate-And- Test, Hill Climbing, Best-First Search, A*Algorithm, Problem Reduction, AO*Algorithm, Constraint Satisfaction, Means-Ends Analysis
Procedural Vs Declarative Knowledge, Representations & Approaches to Knowledge Representation, Forward Vs Backward Reasoning, Matching Techniques, Partial Matching, Fuzzy Matching Algorithms and RETE Matching Algorithms; Logic Based Programming- AI Programming languages: Overview of LISP, Search Strategies in LISP,Pattern matching in LISP , An Expert system Shell in LISP, Over view of Prolog, Production System using Prolog.
Propositional Logic, First Order Predicate Logic: Representing Instance and is-a Relationships, Computable Functions and Predicates, Syntax & Semantics of FOPL, Normal Forms, Unification &Resolution, Representation Using Rules, Natural Deduction; Structured Representations of Knowledge: Semantic Nets, Partitioned Semantic Nets, Frames, Conceptual Dependency, Conceptual Graphs, Scripts, CYC.
Knowledge and Learning, Learning by Advise, Examples, Learning in problem Solving, Symbol Based Learning, Explanation Based Learning, Version Space, ID3 Decision Based Induction Algorithm, Unsupervised Learning, Reinforcement Learning, Supervised Learning: Perceptron Learning, Back propagation Learning, Competitive Learning, Hebbian Learning, Application-Speech Recognition-Self-driving cars-Virtual Personal Assistant.
Role of Knowledge in Language Understanding, Approaches Natural Language Understanding, Steps in The Natural Language Processing, Syntactic Processing and Augmented Transition Nets, Semantic Analysis, NLP Understanding Systems; Statistical NLP ,Bag of Words Model, POS Tagging, Tokenization, Word Vectorizer, TF-IDF, Named Entity Recognition, Stop Words. Recommendation Systems, Application- Chatbots-Voice Assistants- Case study - Classification and Filtering
Reference Book:
Introduction to Artificial Intelligence & Expert Systems, Patterson, PHI Patrick Henry Winston, Artificial Intelligence, 3rd Edition, AW, 1999 Introduction to Machine Learning - EthemAlpaydin, MIT Press, Prentice hall of India. Elaine Ric, Kevin Knight and Shiv Shankar B. Nair, Artificial Intelligence, 3rd edition, Tata McGraw Hill, 2009 George F. Luger, “Artificial Intelligence-Structures and Strategies for Complex Problem Solvingâ€, 6th edition, Pearson, 2008. Tom M Mitchell, Machine Learning, McGraw Hill Education, McGraw Hill Education; First edition, 2017. Stuart Russell and Peter Norvig “ Artificial Intelligence - A Modern Approach†, Prentice Hall, 4th edition, 2022.
Text Book:
Stuart Russell and Peter Norvig Artificial Intelligence - A Modern Approach, Prentice Hall, 3rd edition, 2011.
