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COURSE INFORMATION FOR CURRENT SEMESTER/TERM

Code KEEE4336

Title Artificial Intelligence, Fuzzy Logic And Neural Networks

Pre-requisite KEEE 2150

Student Learning Time (SLT) 120 hours

Credit 3

Learning Outcomes 1. Apply search methods in arriving at an optimum solution for a
given AI related problems.
2. Apply knowledge based systems, specifically, rules-based sys-
tems, model-based systems and frames for knowledge represen-
tation.

3. Describe logical statements as well as to represent natural lan-
guage statements in first order logic for knowledge representation
as well as a basis for logic programming.
4. Design artificial neural networks, fuzzy logic and genetic algo-
rithm for various AI related problems.
Synopsis Student will be introduced to concepts of artificial intelligence (AI),
search, rule-based systems, logic, theorem proving and Prolog,

knowledge representation, frames, artificial neural networks, fuzzy
logic, genetic algorithm.
Assessment 40 % Continuous Assessments
60 % Final Examination

References George F Luger,Artificial Intelligence, 4th edition, Addison Wesley
(2008)

Patrick H Winston, “Artificial Intelligence”, 3rd edition, Addison Wes-
ley (1990)
Soft Skills Communication Skills (CS1, CS2, CS3)
Critical Thinking & Problem Solving (CT1, CT2, CT3)
Team Working Skills (TS1, TS2)
Lifelong Learning & Information Management (LL1, LL2)
Leadership Skills (LS1, LS2)

UM-PT01-PK03-BR004(BI)-S04