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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)