Vishwakarma Institute of Technology B.E. (Electronics)
Vishwakarma Institute of Technology B.E. (Electronics)
Vishwakarma Institute of Technology B.E. (Electronics)
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Bansilal Ramnath Agarwal Charitable Trust’s<br />
<strong>Vishwakarma</strong> <strong>Institute</strong> <strong>of</strong> <strong>Technology</strong>, Pune – 411 037<br />
Department <strong>of</strong> <strong>Electronics</strong> Engineering<br />
FF No. : 654<br />
EC42102 :: ARTIFICIAL INTELIGENCE<br />
Credits: 03<br />
Prerequsit: NIL<br />
Teaching Scheme: - Theory 3 Hrs/Week<br />
OBJECTIVE:-<br />
• To provide a strong foundation <strong>of</strong> fundamental concepts in Artificial Intelligence<br />
• To provide a basic exposition to the goals and methods <strong>of</strong> Artificial Intelligence<br />
• To enable the student to apply these techniques in applications which involve<br />
perception, reasoning and learning.<br />
Mapping with PEO : 2,3,6,7,8,9<br />
Unit 1 : Introduction To Artificial Intelligence<br />
(6 Hrs)<br />
A) AI task domain, problem representation in AI, Problem characteristics.<br />
B) Game playing using AI.<br />
Unit 2 : Searching Techniques<br />
(9 Hrs)<br />
A) A.I. search process, non-heuristic and heuristic search techniques, , constrain<br />
satisfaction and their applications.<br />
B) Min-max search procedure.<br />
Unit 3 : Knowledge Representation<br />
(8 Hrs)<br />
A) Hierarchy <strong>of</strong> knowledge, types <strong>of</strong> knowledge, knowledge representation, methods for<br />
knowledge representation, predicate logic, Problems on predicate logic.<br />
B) Introduction to PROLOG.<br />
Unit 4 : Planning<br />
(8 Hrs)<br />
A) Components <strong>of</strong> planning system, goal stack planning technique.<br />
B) Nonlinear Planning using Constraint Posting.<br />
Unit 5: AI Tools<br />
(9 Hrs)<br />
A) Expert System Shells, Explanation, and Knowledge Acquisition. Human expert<br />
behaviors, Expert system components, structure <strong>of</strong> expert system, the production system,<br />
how expert system work and Expert system development for particular application.<br />
Natural language processing: Introduction, Syntactic Processing, Semantic Analysis,<br />
Discourse and Pragmatic Processing.<br />
Architectures and functions in ANN, various learning rules. Building an ANN.<br />
B) Building an Expert System<br />
Structure & Syllabus <strong>of</strong> B.E (<strong>Electronics</strong> ) Program – Pattern ‘C11’, Rev01, dt. 2/4/2011<br />
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