ECE 479
Principles of Artificial Intelligence
Course Level
Units
Instructor(s)
Prerequisite(s)
Course Texts
Recommended/Optional:
- Artificial Intelligence: A Modern Approach, Stuart Russell and Peter Norvig. (Not mandatory)
Additional materials will be handed out in class.
Schedule
Course Description
Specific Course Information:
2021-2022 Catalog Data: Provides an introduction to problems and techniques of artificial intelligence (AI). 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; implementing AI systems.
Learning Outcomes
Specific Goals for the Course:
Outcomes of Instruction: By the end of this course the student will be able to:
- The goal of this course is to provide students with an introduction to problems and techniques of artificial intelligence (AI). Computer Engineering majors and students pursuing degrees in other fields benefit by learning how to use problem-solving, knowledge representation, and other AI-based techniques.
Course Topics
Brief list of topics to be covered:
- Introduction: What is Artificial Intelligence?
- Problem Solving
2.1 Problems and Problem Spaces
2.1.1 State space search
2.1.2 Production systems
2.1.3. Control Strategies
2.1.4. Heuristic Search
2.2 Basic Problem Solving Methods
2.2.1 Forward and backward reasoning
2.2.2 Problem trees and graphs
2.2.3. The role of representation
2.2.4 Search methods
2.3 Game Strategies
2.3.1 Minimax
2.3.2 Alpha-Beta Search - Knowledge Representation (KR)
3.1 Principles of KR using predicate logic
3.2 Overview of KR using other logics
2.2 Structured representations of knowledge - Planning
4.1 Blocks world problems
4.2 Representation for planning
4.3 Plan generating systems - Introduction to selected advanced topics, including but not limited to computer-guided surgery, intelligent sensing systems, co-evolution, game theory, and 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:
1. An ability to identify, formulate, and solve complex engineering problems by applying principles of engineering, science, and mathematics.
2. An ability to apply engineering design to produce solutions that meet specified needs with consideration of public health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
6. An ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering judgment to draw conclusions.
7. An ability to acquire and apply new knowledge as needed, using appropriate learning strategies.