Course Name: Artificial Intelligence
Credit Hours: 3-1
Contact Hours: 3-3
Pre-requisites: Object Oriented Programming
Course Introduction:
Artificial Intelligence has emerged as one of the most significant and promising areas of computing. This course focuses on the foundations of AI and its basic techniques like Symbolic manipulations, Pattern Matching, Knowledge Representation, Decision Making, and appreciating the differences between Knowledge, Data, and Code. AI programming language Lisp has been proposed for the practical work of this course.
| CLO No. | Course Learning Outcomes | Bloom Taxonomy |
CLO-1 |
Understand the fundamental constructs of Lisp programming language. | C2 (Understand) |
CLO-2 |
Understand key concepts in the field of artificial intelligence | C2 (Understand) |
CLO-3 |
Implement artificial intelligence techniques and case studies | C3 (Apply) |
Course Outline:
An Introduction to Artificial Intelligence and its applications towards Knowledge-Based Systems; Introduction to Reasoning and Knowledge Representation, Problem-Solving by Searching (Informed searching, Uninformed searching, Heuristics, Local searching, Minmax algorithm, Alpha-beta pruning, Game-playing); Case Studies: General Problem Solver, Eliza, Student, Macsyma; Learning from examples; Natural Language Processing; Recent trends in AI and applications of AI algorithms. Lisp & Prolog programming languages will be used to explore and illustrate various issues and techniques in Artificial Intelligence.
Reference Materials:
- Russell, S. and Norvig, P. “Artificial Intelligence. A Modern Approach”, 3rd ed, Prentice Hall, Inc., 2015.
- Norvig, P., “Paradigms of Artificial Intelligence Programming: Case studies in Common Lisp”, Morgan Kaufman Publishers, Inc., 1992.
- Luger, G.F. and Stubblefield, W.A., “AI algorithms, data structures, and idioms in Prolog, Lisp, and Java”, Pearson Addison-Wesley. 2009.