Artificial Intelligence-Course Content

Artificial Intelligence - COURSE SPECIFICATIONp

Course Title: Artificial Intelligence & Computer Vision
Course Code: SENG-620
Degree Program: BS (Software Engineering) P-IV (1st Semester)
Course rating: 3 credit hours
Pre-requisites: Programming Fundamentals, Data Structures, Mathematics

Lecturer : Dr. Zeeshan Bhatti

Course Objectives:
The objective of this course is to convey the basic issues in artificial intelligence and
computer vision and major approaches that address them.

Syllabus Outline:
Introduction: Artificial Intelligence definition, Introductory study of AI techniques, Problems
and problem spaces production systems, Characteristics, Heuristics. Background, History of
Computer Vision, Images, Representation and Elements of Processing.

Problem Solving Methods: Forward and backward reasoning, Problem trees problem Graphs,
Generate and test hill climbing, Search methods, Problem reduction, Constraint Satisfaction.
Mean ends analysis, Game-playing, Min- max algorithm, Alpha_ beta Heuristics.

Knowledge Representation (Logic & Structured): Representing facts in logic, Predicate logic,
Resolution unification, Question answering, non monotonic reasoning, Statistical and
probabilistic reasoning. Declarative representation, Semantic nets, Frames, Scripts, Procedural
representation.

Problem Solving: Systems planning, System organization, Expert systems, Case studies,
Introduction to Neural networks.

Natural Language Processing: Natural language understanding: Problems in understanding
natural language, syntactic Analysis, Semantic analysis, Understanding multiple sentences,
Language generation, Machine translation.

Computer Vision And Learning: Perception, Techniques used in solving perceptual problems,
Constraint Satisfaction, Waltz algorithms, Learning – random learning and Natural nets, Rote
learning, Learning by parameter adjustment, Concept learning by teaching, Learning through
examples, Learning through mistakes, Learning by analogy, Skill acquisition.

LISP & PROLOG: Introduction to LISP, S-expression, Functions, Function definition,
Recursion, loop Statements, simple programs, Introduction to PROLOG, Facts, Rules,
Variables, Satisfying goals, Lists, Recursive search, Mapping, Backtracking and cut, Simple
programs.

Learning Material/References: 

* Artificial Intelligence: A Modern Approach., 3rd Edition, by S. Russell and P. Norvig,  Prentice-Hall, 2003.  

* Computer Vision : A Modern Approach, D. Forsyth and J. Ponce, Prentice-Hall, 2001