This is an archived handbook for a previous year. The current undergraduate and postgraduate handbooks can be viewed using the links above.

Undergraduate Handbook 2012-2013 (archived)

Module COMP3311: ADVANCED ARTIFICIAL INTELLIGENCE (20 CREDITS)

Department: Computer Science

COMP3311: ADVANCED ARTIFICIAL INTELLIGENCE (20 CREDITS)

Type	Level	Credits	Availability	Module Cap	Location
Open	3	20	Available in 2012/2013	None.	Durham

Pre-requisites

Software Applications (COMP2071).

Corequisites

None.

Excluded Combinations

None.

Aims

To give students a familiarisation with an understanding of a range of subjects within the broad context of Artificial Intelligence

Content

Design of intelligent agents.
Framework for programming agents.
Multi-agent interactions.
Cooperation and other interactions.
Introduction to automated reasoning.
The logical bases of reasoning methods.
Automated and interactive reasoning.
Systems and applications of mechanised reasoning.

Learning Outcomes

Subject-specific Knowledge

By the end of the modules students will: Understand how Artificial Intelligence methods impact on the different problem areas in two topic areas.
Have knowledge of different paradigms and techniques relevant to each of the two topics.
Understand how Artificial Intelligence is relevant to new technology and technological developments in each of the two topics.

Subject-specific Skills

Demonstrate, for each of the two topics, that they have conducted research and self-study to further their knowledge beyond the taught materials.

Key Skills

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

Lecturing demonstrates what is required to be learned and the applications of the theory to practical examples.
Homework problems identify areas where further independent research should be conducted.
Summative examinations test the knowledge acquired and the students' ability to use this knowledge to solve complex problems.

Teaching Methods and Learning Hours

Activity	Number	Frequency	Duration	Total Hours
Lectures	40	2 per week	1 hour	40
Reading and Preparation				160
Total				200

Summative Assessment

Component	Component Weighting	Element	Length/Duration	Element Weighting	Resit Opportunity
Coursework	30%	Practical work		100%	No
Examination	70%	Examination	1.5 hours	100%	No

Formative Assessment

Example exercises given through the course. Additional revison lectures may be arranged in the modules lecture slots in the 3rd term.

Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.