Programme: M.Tech ARTIFICIAL INTELLIGENCE Semester: FIRST Course: MTAIML12

Mon: 09:00-10:40, Wed: 10:40-11:30 Class Room: SF3

DECEMBER 2022

UNIT-I:

Introduction to artificial intelligence: Introduction, history, intelligent systems, Turing Test, Role of Knowledge, AI applications, tic-tac-tie game playing, current trends in AI,

Problem solving: state-space search and control strategies: Introduction, general problem solving, characteristics of problem, AI problem solving as state space search, exhaustive searches, heuristic search techniques, Hill climbing , A* algorithms,

JANUARY 2022

UNIT-II:

Logic and Theorem Proving concepts: Introduction, propositional calculus, proportional logic, natural deduction system, axiomatic system, semantic tableau system in proportional logic, resolution refutation in proportional logic, predicate logic

UNIT-III:

Problem reduction and game playing: Introduction to problem reduction, AO* algorithm, constraint satisfaction algorithm, Cryptarithmetic Problem solving, Means Ends analysis, game playing, Min-Max algorithm for game playing, alpha-beta pruning, iterative-deepening, two-player perfect information games,

FEBRUARY 2022

UNIT-IV

Representation of Knowledge with Rules: Production System, Forward versus Backward chaining, Rule Matching and chain control, Non-Monotonic reasoning, Truth maintenance systems

Mid Exam – 1

UNIT-V:

Uncertain Reasoning: Probability theory: Introduction, probability theory, Bayes theorem, Bayesian belief networks, certainty factor theory, Dempster-Shafer theory, Statistical Inference

MARCH 2022

UNIT-VI:

Knowledge representation: Introduction, approaches to knowledge representation, knowledge representation using semantic network, extended semantic networks for KR, knowledge representation using frames, advanced knowledge representation techniques: Introduction, conceptual dependency theory, script structure, cyc theory, case grammars, semantic web.

APRIL 2022

UNIT-VII:

Planning: Overview, Blocks world as example, components of planning system, Goal stack planning, Nonlinear planning, Hierarchical planning, Reactive Systems

Expert Systems: Representing and using Domain knowledge, examples of expert systems, Expert system Architectures, Components, Building an expert system, Expert system shells

Mid Exam – 2

Text Books:

1. Artificial intelligence, A modern Approach, 2nded, Stuart Russel, Peter Norvig, Prentice Hall

2. Artificial Intelligence- 3^rd Edition, Rich, Kevin Knight, Shiv Shankar B Nair, TMH

3. Introduction To Artificial Intelligence And Expert Systems, 1^st Edition, Patterson, Pearson India, 2015

Reference Books:

1. Artificial intelligence, structures and Strategies for Complex problem solving, 5^th Edition, George F Lugar,PEA

2. Introduction to Artificial Intelligence, Ertel, Wolf Gang, Springer, 2017

3. Artificial Intelligence, SarojKaushik, 1^st Edition, CENGAGE Learning, 2011

ASSIGNMENT 1: Available here on 24-12-2022 and Submission Closes 30-12-2022 [5 marks]

ASSIGNMENT 2: Available here on 21-02-2023 and Submission Closes 28-02-2023 [5 marks]

Send only one pdf file to slnvizag@gmail.com keeping your registered number in subject line

Plagiarism guidelines are as per the University norms. Late submission will attract one negative mark for each day.