Module 11351 (2003)

Syllabus page 2003/2004

06-11351
AI Programming B

Level 1/C

Shelia Glasbey
10 credits in Semester 2

Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus


The Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)

Changes and updates

Assessment of Learning Outcomes changed; syllabus updated.


Relevant Links


Outline

This module continues the development of AI programming skills using the language Pop-11. More advanced techniques involving recursion, grammar, database and the implementation of search strategies will also be introduced.


Aims

The aims of this module are to:

  • increase the level of the students' understanding of the pop-11 programming language
  • improve the level of sophistication of students' programming skills
  • expose the students to a number of fundamental AI techniques in a practical context

Learning Outcomes

On successful completion of this module, the student should be able to: Assessed by:
1 demonstrate a practical understanding of the pop-11 programming language In-lab test, mini-project
2 demonstrate an ability to use the Poplog development environment effectively In-lab test, mini-project
3demonstrate a practical understanding of how to implement a number of classic AI programming techniques In-lab test, mini-project
4 show an ability to break down programming problems into component parts In-lab test, mini-project

Restrictions, Prerequisites and Corequisites

Restrictions:

None

Prerequisites:

None

Co-requisites:

06-11349 (AI Programming A) (linked module), 06-11352 (AI Techniques A), 06-11353 (AI Techniques B)


Teaching

Teaching Methods:

1 hr lecture, 4 hrs practical programming workshops/tutorials per week

Contact Hours:

55


Assessment

  • Supplementary (where allowed): As the sessional assessment
  • Assessed practical work (100%), divided equally between this module and 06-11349 (AI Programming A). Students who fail these linked modules but achieve at least 30% will be allowed to resit, by means of a software mini-project. Students whose mark is below 30% will be required to repeat the modules in the following academic year.

Recommended Books

TitleAuthor(s)Publisher, Date
Online tutorial material, supporting program libraries
Artificial Intelligence through SearchC Thornton & B du BoulayIntellect, Oxford, 1992

Detailed Syllabus

Not applicable

Last updated: 16 Mar 2004

Source file: /internal/modules/COMSCI/2003/xml/11351.xml

Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus