CS420 — Artificial Intelligence (elective)

Credits: 1 unit (4 credit hours)
Contact Hours: 3 lecture
Instructor: Professor Sofia Serrano
Last Taught: Fall 2024
Text Book: Artificial Intelligence: A Modern Approach (4th Ed.)
By Stuart Russell and Peter Norvig. (Prentice Hall, 2020)
Description: An introduction to the study of intelligence as computation. Topics include problem-solving techniques, heuristic searches, knowledge representation, and learning from examples. 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