Artificial Intelligence

by Neeta Deshpande

Introduction : Definition, What is A.I? Foundation of A.I., History, Intelligent Agents, Agent architecture, A. I. Application (E Commerce &Medicine), A. I. Representation, Properties of internal representation, Future of A.I., Production System, Issue in design of search programs Logic Programming : Introduction, Logic, Logic Programming, Forward and Backward resoning, Forward and Backward chaining rules. Heuristic Search Techniques : Heuristic search , Hill Climbing, Best first search, mean and end analysis, constraint Satisfaction, A* and AO* Algorithm. Game Playing : Minimax search procedure, Alpha-beta cutoffs, Waiting for quiescence, Secondary search Knowledge Representation : Basic of knowledge representation, knowledge representation paradigms, Propositional logic, Inference Rules in Propositional logic, Knowledge representation using Predicate logic : Predicate calculus, Predicate and arguments, ISA hierarchy, Frame notation, Resolution, Natural deduction. Knowledge Representation using Non Montionic Logic : TMS ( Truth Maintenance System ), Statistical and probabilistic reasoning Fuzzy- Logic ,Structure knowledge representation, Semantic-net, Frames, Conceptual dependency, Script. Learning : What is Learning? Types of Learning (Rote, Direct instruction analogy, Induction, Deduction) Planning : Block world, Strips, Implementation using goal stack, Non linear planning with goal stacks, Hierarichial planning, least commitment strategy. Advance AI Topics Natural Language Processing : Introduction, Steps in NLP, Syntactic Processing, ATN, RTN, Semantic analysis, Discourse &Pragmatic processing. Pereception Perception , Action, Robot Architecture. Neural Networks : Introduction to neural networks and perception-qualitative analysis, Neural net architecture and applications. Expert system : Utilization and functionality, Architecture of expert system, Knowledge representation, Two case studies on expert systems.

478 pages, Paperback

Published January 1, 2008