Simon Fraser University
Engaging the World

Course Outlines

Fall 2018 - CMPT 310 D200

Artificial Intelligence Survey (3)

Class Number: 8383

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 4 – Dec 3, 2018: Mon, Wed, Fri, 3:30–4:20 p.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). We introduce basic concepts of machine learning, such as decision trees and neural nets. Probability as a mechanism for handling uncertainty in AI will be presented, with a focus on Bayesian networks.

Topics

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

Grading

NOTES:

The grade is based on assignments 40%, exams 50%, quizzes 10%. Assignments are a mix of programming and conceptual exercises. The prerequisites are important for achieving a satisfactory grade in this course.

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: Structures and Strategies for Complex Problem Solving
  • 6th Edition
  • 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://students.sfu.ca/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