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Artificial Intelligence (Open Elective) : Unit-Ii

This document outlines the units of study for an Artificial Intelligence course. The six units cover topics such as introduction to AI, problem solving techniques, logic concepts, knowledge representation, expert systems and applications, and uncertainty measures including probability theory and fuzzy logic. Problem solving techniques include state-space search, heuristic search, and game playing strategies. Knowledge representation approaches like semantic networks and frames are examined. The roles of expert systems, rule-based systems, and uncertainty calculation in Bayesian belief networks and fuzzy logic are also discussed.

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Radha Krishnan
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273 views1 page

Artificial Intelligence (Open Elective) : Unit-Ii

This document outlines the units of study for an Artificial Intelligence course. The six units cover topics such as introduction to AI, problem solving techniques, logic concepts, knowledge representation, expert systems and applications, and uncertainty measures including probability theory and fuzzy logic. Problem solving techniques include state-space search, heuristic search, and game playing strategies. Knowledge representation approaches like semantic networks and frames are examined. The roles of expert systems, rule-based systems, and uncertainty calculation in Bayesian belief networks and fuzzy logic are also discussed.

Uploaded by

Radha Krishnan
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© © All Rights Reserved
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III Year – II Semester

ARTIFICIAL INTELLIGENCE
(Open Elective)
UNIT-I:

Introduction to artificial intelligence: Introduction, history, intelligent systems, foundations of AI,


applications, tic-tac-tie game playing, development of AI languages, current trends in AI

UNIT-II:

Problem solving: state-space search and control strategies : Introduction, general problem
solving, characteristics of problem, exhaustive searches, heuristic search techniques,
iterativedeepening a*, constraint satisfaction Problem reduction and game playing: Introduction,
problem reduction, game playing, alpha beta pruning, two-player perfect information games

UNIT-III:

Logic 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-IV:

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

UNIT-V:

Expert system and applications: Introduction phases in building expert systems, expert system
versus traditional systems, rule-based expert systems blackboard systems truth maintenance
systems, application of expert systems, list of shells and tools

UNIT-VI:

Uncertainty measure: probability theory: Introduction, probability theory, Bayesian belief


networks, certainty factor theory, dempster-shafer theory Fuzzy sets and fuzzy logic:
Introduction, fuzzy sets, fuzzy set operations, types of membership functions, multi valued logic,
fuzzy logic, linguistic variables and hedges, fuzzy propositions, inference rules for fuzzy
propositions, fuzzy systems.

TEXT BOOKS:
1. Artificial Intelligence- Saroj Kaushik, CENGAGE Learning,
2. Artificial intelligence, A modern Approach , 2nded, Stuart Russel, Peter Norvig, PEA
3. Artificial Intelligence- Rich, Kevin Knight, Shiv Shankar B Nair, 3rded, TMH 4. Introduction
to Artificial Intelligence, Patterson, PHI
REFERNCE BOOKS:
1. Atificial intelligence, structures and Strategies for Complex problem solving, -George F
Lugar, 5thed, PEA
2. Introduction to Artificial Intelligence, Ertel, Wolf Gang, Springer
3. Artificial Intelligence, A new Synthesis, Nils J Nilsson, Elsevier

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