Artificial Intelligence
Course Outline

Course Material
• Text books:
– Artificial Intelligence: Structures and Strategies
for Complex Problem Solving (4th ed.),
George F. Luger, Addison-Wesley
• http://www.cs.unm.edu/~luger/ai-final/
– Artificial Intelligence, A Modern Approach,
Stuart Russell and Peter Norvig, Prentice Hall
• http://aima.cs.berkeley.edu/

Course Description
• Artificial Intelligence is the subfield of computer
science concerned with automating tasks that
would require "intelligence" if performed by
people.
• AI is a highly eclectic field, with roots in
mathematics, logic, psychology, philosophy, and
engineering.
• The goal of this course is to introduce and survey
the field of Artificial Intelligence, paying special
attention to foundational concepts and theories.
• In addition, current trends and approaches in AI
research will be studied

Course Outline
• Course overview and Introduction to AI
• AI history
• LOGIC PROGRAMMING
• Predicate logic, Prolog
• Prolog Basics
• Prolog: unification, Resolution, lists
• More Prolog: built-in predicates, Operators
• AI AS SEARCH
• State spaces, uninformed strategies
• Constraint-based search

• Heuristics, Informed strategies
• Optimization problems, Game Trees
• REPRESENTATION & AI
• Semantic nets, Frames
• Expert Systems, Uncertainty
• Rule-based Reasoning
• MACHINE LEARNING
• Connectionist Models
• Emergent Models
• Genetic Algorithms, a-life
• Case Studies: Eliza, Mycin
• Student presentations
Course Outline (contd.)

Questions & Answers
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