Durham University
Programme and Module Handbook

Undergraduate Programme and Module Handbook 2013-2014 (archived)

Module COMP3311: ADVANCED ARTIFICIAL INTELLIGENCE (20 CREDITS)

Department: Computer Science

COMP3311: ADVANCED ARTIFICIAL INTELLIGENCE (20 CREDITS)

Type Open Level 3 Credits 20 Availability Available in 2013/14 Module Cap None. Location Durham

Prerequisites

  • Software Applications (COMP2071).

Corequisites

  • None.

Excluded Combination of Modules

  • 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: Coursework Component Weighting: 30%
    Element Length / duration Element Weighting Resit Opportunity
    Practical work 100% No
    Component: Examination Component Weighting: 70%
    Element Length / duration Element Weighting Resit Opportunity
    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.

    ■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University