Spring 2019 - CMPT 310 D200

Artificial Intelligence Survey (3)

Class Number: 6514

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 3 – Apr 8, 2019: Mon, Wed, Fri, 12:30–1:20 p.m.
    Burnaby

  • Exam Times + Location:

    Apr 24, 2019
    Wed, 8:30–11:30 a.m.
    Burnaby

  • Prerequisites:

    CMPT 225 and (MACM 101 or ENSC 251 and ENSC 252)).

Description

CALENDAR DESCRIPTION:

Provides a unified discussion of the fundamental approaches to the problems in artificial intelligence. The topics considered are: representational typology and search methods; game playing, heuristic programming; pattern recognition and classification; theorem-proving; question-answering systems; natural language understanding; computer vision. Students with credit for CMPT 410 may not take this course for further credit.

COURSE DETAILS:

Artificial Intelligence (AI) is the part of computer science concerned with systems that learn, reason and make/support decisions. The goal of this course is to provide students with a survey of different aspects of artificial intelligence. A variety of approaches with general applicability will be developed. We will start with the theory of optimal decision-making, both for single agents (expected utility) and multiple agents (game theory). The next topic is searching for solutions to complex decision and planning problems (search strategies and heuristics). Symbolic logic will be presented as a formalism for representing knowledge in AI systems. Probability as a mechanism for handling uncertainty in AI will be presented, with a focus on Bayesian networks. We will introduce basic concepts of machine learning, such as decision trees and neural nets.

Topics

  • Search
  • Logic
  • Game playing
  • Planning
  • Reasoning under uncertainty (probability)
  • Bayesian networks
  • Utility theory, Decision networks
  • Learning

Grading

NOTES:

To be discussed the first week of classes

Students must attain an overall passing grade on the weighted average of exams in the course in order to obtain a clear pass (C- or better).

Materials

MATERIALS + SUPPLIES:

  • Artificial Intelligence: Foundations of Computational Agents, David L. Poole and Alan Mackworth, New York : Cambridge University Press, 2010, 9780521519007
  • Artificial Intelligence (6th Edition). Structures and Strategies for Complex Problem Solving, George Luger, Addison Wesley, 2009, 9780321545893

REQUIRED READING:

Artificial Intelligence: A Modern Approach (3rd Edition)
Stuart J. Russell, Peter Norvig
Prentice Hall, 2010
ISBN: 9780136042594

Registrar Notes:

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS