Download CS4618 - Computer Science

CS4618 Artifical Intelligence I
Credit Weighting: 5
Teaching Period(s): Teaching Period 1
Pre-requisite(s): None
Co-requisite(s): None
Teaching Methods: 24 x 1 hour(s) lectures; 10 hours laboratory/tutorial sessions
Module Co-ordinator: Head, Department of Computer Science
Lecturer(s): Staff, Department of Computer Science
Module Objective: Students will explore the state of the art in Artificial Intelligence (AI).
Module Content: Topics will be selected from the following and others: advanced AI search; natural
language processing; randomised search heuristics (e.g., swarm intelligence; evolutionary
computation); multi-agent systems.
Learning outcomes: On successful completion of this module, students should be able to:
*demonstrate a broad knowledge of modern AI theory and applications, including a sense of
the successes and failures
*apply advanced AI search techniques
*assess if a problem is amenable for solution by specific AI techniques
*decide where the application of randomised search heuristics is appropriate for solving a
problem
*adapt general randomised search heuristics to a specific search problem
Assessment: Total Marks 100: End of Year Written Examination 80 marks; Continuous Assessment
20 marks
Compulsory Elements: End of Year Written Examination; Continuous Assessment
Penalties (for late submission of Course/Project Work etc.): Work which is submitted late shall be
assigned a mark of zero (or a Fail Judgement in the case of Pass/Fail modules).
Pass Standard and any Special Requirements for Passing Module: 40%
End of Year Written Examination Profile: 1 x 1.5 hr(s) paper(s)
Requirements for Supplemental Examination: 1 x 1.5 hr(s) paper(s) to be taken in Autumn. Marks in
passed element(s) of Continuous Assessment are carried forward, Failed element(s) of Continuous
Assessment must be repeated (as specified by the Module Coordinator)