EECS 4740 - Artificial Intelligence Course Syllabus
Credits/Contact Hours
3 credit hours & 160 minutes lecture contact per week.
Textbook
Artificial Intelligence: A Modern Approach - The Intelligent Agent Book 3rd Ed. by S. Russell and P. Norvig, Prentice-Hall, 2010.
Course Information
This course explores the topic of intelligent software agents with an emphasis on
hands-on design of adaptive problem-solving agents for environments of increasing
complexity ranging from single-agent computer games to complex real-world multi-agent
environments.
Prerequisites: EECS 2510
Elective course.
Specific Goals - Student Learning Objectives (SLOs)
Upon completion of this course, students will be able to:
1. Develop an abstract representation for a problem in a given domain which is appropriate
for AI
2. Learn the computational and mathematical theory, and application of fundamental
AI algorithms
3. Identify and apply the most appropriate AI algorithm for a given problem domain
4. Develop familiarity with case studies, benchmark problems and solution methodologies
in AI
5. Use a software tool to empirically validate the solutions based on AI methodologies
6. Understand the tradeoff between computational complexity and solution quality.
Topics
- Introduction to AI
- Search Methods: Uninformed Search, Informed Search, Path Search vs. Local Search
- Game Playing Through Search: Minimax and Alpha-Beta
- Constraint Satisfaction
- Inductive Learning
- Decision Trees
- Artificial Neural Networks
- Propositional & First Order Logic
- Planning