Course Code: CSE 315

Course Code: CSE 315

Publish Date: 
Thursday, August 13, 2015
Department: 
Bachelor of Science, Electronics and Telecommunication Engineering (ETE)

Course Code: CSE 315
Course Name: Artificial Intelligence
Prerequisite: None
Credit Hours: 3.00

Detailed Syllabus:

Importance of AI, Knowledge Representation: Definition and importance of knowledge, representing single facts in logic, resolution non-monotonic reasoning, Dealing within inconsistencies and uncertainties, dempster shafrer theory, Ad-Ho methods, Heuristic reasoning methods, structural representation of knowledge graphs, frames and related structures. Neural Networks: Biological neuron, Artificial neurons and neural networks, Learning processes. Perceptron, multilayer layer perceptron, Bi-directional associative memory, Back propagation method, Self-organizing Kohonen networks, Hopfield neural network. Fuzzy Logic: Fuzzy set and control theory. Fuzzy inference, Fuzzy logic expert systems, Fuzzy associative memory, Fuzzy neural control. General algorithm, Pattern Recognition: Recognition and classification process, learning classification patterns, recognizing and understanding speech. Expert System: architectures, model based system, constraint satisfaction. Introduction to neural networks, learning algorithms and models.