Computer Science (COMP) 456

Artificial Intelligence and Expert Systems (Revision 3)

COMP 456 Course Web site

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Delivery Mode: Individualized study online

Credits: 3

Area of Study: Science

Prerequisite: MATH 215 or MATH 216, COMP 272, and COMP 361.

Note: Students who are concerned about not meeting the prerequisites for this course are encouraged to contact the course coordinator before registering.

Students in this course are required to contact their tutor using email or the course (Moodle) forums. Please see the Tutor and Coordinator Support page for more information.

Centre: School of Computing and Information Systems

SCIS Orientation

COMP 456 sample

Course website

CCIS Software and Hardware Requirements


COMP 456 has a Challenge for Credit option.

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Overview

The course deals with two broad topics: Prolog programming language and artificial intelligence (with special attention to expert systems). The course starts by introducing Prolog, how it works, how programs are developed, techniques to handle complex data structures, built-in procedures, techniques of good programming, and techniques used in artificial intelligence.

Then the course delves into some central areas of artificial intelligence such as problem solving, expert systems, natural language processing, and machine learning. Throughout the course, the student will frequently be required to work with examples.

Learning Objectives

The main objectives of this course are:

  • explain knowledge representation concepts.
  • introduce logic programming using the declarative model of Prolog.
  • explain problem solving and reasoning strategies in AI systems.
  • explain the design and implementation of expert system.
  • provide an introduction to natural language processing.
  • provide an introduction to machine learning.

Learning Outcomes

Students successfully completing this course will be able to:

  • explain the basic concepts of knowledge representation (facts, rules, etc.).
  • explain the relation between Prolog and formal logic.
  • develop Prolog programs using different data structures, databases, and built-in procedures.
  • debug and improve efficiency of Prolog programs using recursion and accumulators.
  • implement different algorithms for sorting lists and processing binary trees, dictionaries, and graphs.
  • implement problems solving strategies using a graph-based model such as depth-first and breadth-first.
  • use the A* algorithm for solving problems and introduce some advanced versions of A* such as IDA*, RBFS.
  • represent problems using an AND/OR graph or constraint logic programming.
  • explain the fundamentals of expert systems and knowledge representation with uncertainty.

Outline

COMP 456 consists of the following nine units.

  • Unit 1 presents the syntax and the control structures of the Prolog language.
  • Unit 2 discusses operations on lists, operator notation and arithmetic, and data abstraction.
  • Unit 3 presents the “cut” facility used for preventing backtracking and introduces the concept of “negation as failure”.
  • Unit 4 presents more built-in procedures and control facilities.
  • Unit 5 presents algorithms for operations in lists, trees and graphs.
  • Unit 6 presents different techniques for problem solving and for representing decomposable problems.
  • Unit 7 presents the fundamental concepts of knowledge representation and expert systems.
  • Unit 8 introduces the concepts related to processing natural language using grammar rules.
  • Unit 9 introduces the concept of machine learning.

Evaluation

There are three tutor-marked exercises (TMEs), a software project, and a final examination in this course. The first TME, to be completed after Unit 3, will assess the student's abilities in Prolog programming in general. The second, which falls after Unit 6, gauges the student's abilities in some artificial intelligence and problem solving fundamentals and how the student may bring them to life through Prolog. The third TME is to be completed after Unit 8, and evaluates the student's understanding and perception of some advanced artificial intelligence areas such as natural language processing.

To receive credit for COMP 456, you must achieve a course composite grade of at least "D" (50 percent) (a grade of at least 50 percent on the invigilated final examination and an average grade of at least 50 percent on the assignments and a grade of at least 50 percent on the project). The weighting of the composite grade is as follows:

TME 1 TME 2 TME 3 Project Final Exam Total
10% 15% 15% 20% 40% 100%

To learn more about assignments and examinations, please refer to Athabasca University's online Calendar.

Course Materials

Textbook

Ivan Bratko. 2001 PROLOG Programming For Artificial Intelligence (3rd ed. Printed 2001). England. Addison Wesley - ISBN 0-201-40375-7.

Supplementary Reading

George F. Luger, 2005. Artificial Intelligence: Structures and Strategies for Complex Problem Solving (5th Edition). Addison-Wesley, ISBN-10: 0321263189.

Michael Negnevitsky, 2005. Artificial Intelligence: A Guide to Intelligent Systems (2nd Edition). Addison-Wesley, ISBN-10: 0321204662.

Other material

The remainder of the learning materials for COMP 456 are distributed in electronic format. At this time, the material includes:

  • COMP 456 Study Guide
  • detailed description of the requirements for the individual tutor-marked exercises
  • a course evaluation form
  • links to a variety of resources on the World Wide Web.

Additional supporting materials of interest to students of COMP 456 may occasionally be made available electronically.

Special Course Features

COMP 456 is offered by computer mediated communications mode, and can be completed at the student's workplace or home. Students are required to buy their own version of a Prolog compiler (the exact version will be determined by the course tutor).

Challenge for Credit Course Overview

The Challenge for Credit process allows students to demonstrate that they have acquired a command of the general subject matter, knowledge, intellectual and/or other skills that would normally be found in a university level course.

Full information for the Challenge for Credit can be found in the Undergraduate Calendar.

Challenge Evaluation

To receive credit for the COMP 456 challenge, you must achieve a grade of at least “D” (50 per cent) on the examination and 50 per cent on the project.

Project Exam Total
50% 50% 100%

Undergraduate Challenge for Credit Course Registration Form

Athabasca University reserves the right to amend course outlines occasionally and without notice. Courses offered by other delivery methods may vary from their individualized-study counterparts.

Opened in Revision 3, July 21, 2008.

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