Module 18185.2 (2005)
Syllabus page 2005/2006
06-18185
AI Programming
Level 1/C
John Barnden
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.)
Relevant Links
Detailed web pages for 2005 Semester 2 (Spring)
Outline
This module introduces general procedural and functional programming techniques as well as basic AI programming styles (including list manipulation and pattern matching) using the language Pop-11. More advanced techniques involving recursion, grammar, databases and the implementation of search strategies will also be introduced.
Aims
The aims of this module are to:
- introduce general procedural and functional programming techniques using the language Pop-11, assuming no prior knowledge of computer programming
- introduce basic AI programming techniques (including list manipulation, pattern matching and databases)
- improve the level of sophistication of students' programming skills
- expose 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 | break down programming problems into component parts | In-lab tests, assessed exercises, mini-project |
| 2 | write simple modular programs in the language Pop-11 | In-lab tests, assessed exercises, mini-project |
| 3 | use the Poplog development environment effectively | In-lab tests, assessed exercises, mini-project |
| 4 | apply and implement some classic AI programming concepts, representations and techniques, including those presented in other AI modules | In-lab tests, assessed exercises, mini-project |
| 5 | demonstrate relevant software engineering/software development skills including: producing a proposal, planning a program, specifying a program, testing, tracing, debugging and writing reports | Mini-project |
Restrictions, Prerequisites and Corequisites
Restrictions:
None
Prerequisites:
None
Co-requisites:
06-18188 (Introduction to AI), 06-18184 (AI & Cognitive Science)
Teaching
Teaching Methods:
1 hr lecture, 4 hrs practical programming workshops/tutorials per week
Contact Hours:
Assessment
- Supplementary (where allowed): As the sessional assessment
- Assessed practical work (100%). Students who fail this module 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 module in the following academic year.
Recommended Books
| Title | Author(s) | Publisher, Date |
| Online tutorial material, supporting program libraries | ||
| Artificial Intelligence through Search | C Thornton & B du Boulay | Intellect, Oxford, 1992 |
Detailed Syllabus
- Poplog, XVed, Pop-11, On-line documentation, compilation, simple expressions
- Data types, comments, variables, printing, assignments, arithmetic operators
- Stack and stack errors, procedures, built-in procedures
- List manipulation, pattern matching
- Conditionals, iteration
- Advanced list manipulation and pattern matching techniques
- Designing solutions to practical problems, choosing representations and datatypes, designing algorithms
- Recursion
- Knowledge representation
- Implementing search strategies (depth/breadth-first, heuristic functions, hillclimbing, etc.)
- Natural language processing, grammar and parsing.
- Planning and rule-based reasoning.
Last updated: 7 Jan 2005
Source file: /internal/modules/COMSCI/2005/xml/18185.xml
Links | Outline | Aims | Outcomes | Prerequisites | Teaching | Assessment | Books | Detailed Syllabus