CS420 — Artificial Intelligence (elective)

Credits: 1 unit (4 credit hours)
Contact Hours: 3 lecture
Instructor: Professor Chun Wai Liew
Last Taught: Fall 2013
Text Book: Artificial Intelligence: A Modern Approach (3rd Ed.)
By Stuart Russell and Peter Norvig. (Prentice Hall, 2009)
Description: An introduction to the study of intelligence as computation. Topics include problem-solving techniques, heuristic searches, and knowledge representation. Lecture/laboratory.
Prerequisites: CS202 (Analysis of Algorithms) and
CS205 (Software Engineering)

Specific Course Goals:

After successfully completing this course, the student will be able to:

  • Students will demonstrate the ability to analyze, design, apply and use AI techniques on projects.

Student Outcomes:

ABET/CAC Outcome 1 Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
ABET/CAC Outcome 6 Apply computer science theory and software development fundamentals to produce computing-based solutions.

Topics covered:

  • Agents and Problem Domains
    • Problem Domains
    • Specification of Agents
    • Types of Environments
    • Categories of Agents
  • game trees:
    • minmax,
    • alpha-beta
  • search:
    • depth first search,
    • breadth first search,
    • heuristic search,
    • A*
  • probabilistic reasoning:
    • bayesian nets,
    • markov models
  • learning:
    • decision trees,
    • neural nets,
    • classification,
    • reinforcement learning
  • first order logic:
    • resolution,
    • modus ponens
  • planning:
    • classical planning,
    • graphplan
  • robotics:
    • Robotic Perception
    • Movement Planning
    • Planning Uncertain Movements
    • Robotic Software Architectures