ECE 479
Principles of Artificial Intelligence
Course Level
Units
Prerequisite(s)
Course Texts
Russell, Stuart, and Peter Norvig. Artificial Intelligence: A Modern Approach. 3rd ed. Pearson, 2009.
Schedule
Course Description
Introduction to problems and techniques of artificial intelligence (AI). Topics inlcude automated problem solving, methods and techniques; search and game strategies; knowledge representation using predicate logic; structured representations of knowledge; automatic theorem proving, system entity structures, frames and scripts; robotic planning; expert systems; and implementing AI systems.
May be convened with ECE 579.
Learning Outcomes
By the end of this course, the student will be able to:
- Demonstrate the ability to solve combinatorially complex problems by using heuristic techniques
- Construct knowledge representations and apply them as the foundation for design and analysis of complex computer-based systems
- Demonstrate an understanding of planning techniques, construct plans and plan-generating systems
- Design knowledge-based systems
- Design and implement reasoning engines and theroem provers
Course Topics
What is artificial intelligence?
Problems and problem spaces
- State space search
- Production systems
- Control strategies
- Heuristic search
Basic problem-solving methods
- Forward and backward reasoning
- Problem trees and graphs
- The role of representation
- Search methods
Game strategies
- Minimax
- Alpha beta search
Knowledge representation (KR)
- Principles of KR using predicate logic
- Overview of KR using other logics
- Structured representations of knowledge
Planning
- Blocks world problems
- Representation for planning
- Plan generating systems
Advance topics including, but not limited to:
- Computer-guided surgery
- Intelligent sensing systems
- Coevolution
- Game theory
- Big data science
Relationship to Student Outcomes
ECE 479 contributes directly to the following specific electrical and computer engineering student outcomes of the ECE department:
- Ability to apply knowledge of mathematics, science and engineering (medium)
- Ability to design and conduct experiments, as well as to analyze and interpret data (medium)
- Ability to design a system, component or process to meet desired needs within realistic constraints, such as economic, environmental, social, political, ethical, health and safety, manufacturability and sustainability (medium)
- Ability to function on multidisciplinary teams (low)
- Ability to identify, formulate and solve engineering problems (high)
- Understanding of professional and ethical responsibility (low)
- Ability to communicate effectively (medium)
- Broad education necessary to understand the impact of engineering solutions in a global, economic, environmental and societal context (medium)
- Recognition of the need for, and an ability to engage in, life-long learning (medium)
- Knowledge of contemporary issues (medium)
- Ability to use the techniques, skills and modern engineering tools necessary for engineering practice (high)