ECS 170: Introduction to Artificial Intelligence

ECS 170
Introduction to Artificial Intelligence
Effective Term
2020 Spring Quarter
Learning Activities
Lecture: 3 hours
Discussion: 1 hour
Design and implementation of intelligent computer systems. Knowledge representation and organization. Memory and inference. Problem solving. Natural language processing. GE Prior to Fall 2011: SciEng. GE: SE.
ECS 060 or ECS 032B or ECS 036C
Enrollment Restrictions
Pass One open to Computer Science and Computer Science & Engineering Majors only; Pass Two open to undergraduate students only.

Summary of Course Content

  1. Informed Search
    1. Time and space complexity of uninformed search
    2. The A* Informed search algorithm and inventing admissible heuristics
    3. Proofs of optimality and optimal efficiency
  2. Adversarial Search
    1. Zero-sum games
    2. Game trees and evaluation functions
    3. The mini-max algorithm
    4. The alpha-beta algorithm
    5. Extensions to multi-player and games of chance
    6. Proofs of best case, worst case and expected case time complexity
  3. Graphical Models of Learning
    1. Page rank models and random walks on graph
    2. Basic propositional graphs
    3. Three types of queries
    4. The intractability of general inference of graphs
    5. Approximation algorithms using MCMC samplers
  4. Connectionist Architectures
    1. Perceptrons, Linear Units and Sigmoid functions
    2. Learning single units
    3. Learning networks of units
  5. Reinforcement Learning
    1. Markov decision processes
    2. Cumulative discount rewards
    3. Learning Q-tables
    4. Proofs of convergence and anytime behavior

Illustrative Reading
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 3rd edition, Prentice Hall, 2009.

Potential Course Overlap

Course Category