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Course
Pro-forma
Bachelor of Engineering (Electrical)
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
systems, model-based systems and frames for knowledge
representation.
3.
Describe logical statements as well as to represent natural
language statements in first order logic for knowledge
representation as well as a basis for logic programming.
4.
Formulate artificial neural networks, fuzzy logic and genetic
algorithm 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
1.
George F Luger,Artificial Intelligence, 4th edition, Addison
Wesley (2008)
2.
Patrick H Winston, “Artificial Intelligence”, 3rd edition,
Addison Wesley (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)