Introduction to Artificial Intelligence (COMP30030)

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General

Credits:

Level:

Semester:

Semester One

Subject:

Computer Science

School:

Computer Science & Informatics

Module Coordinator:

Dr Lorraine McGinty

This module offers a very broad introduction to the fundamental concepts and techniques of artifical intelligence, and aims to provide the student with the ability to assess and apply some of the basic techniques used in Artificial Intelligence (AI). Some of the topics covered include: Knowledge Representation, Problem Solving & Search, Game Playing, Planning, Machine Learning and Classification, Knowledge Reasoning, and Recommender Systems.

Outcomes

By the end of this module a student should be able to:- Explain the underlying principles, and evaluate the advantages and limitations, of the AI approach to problem solving.- Describe and implement a range of search algorithms and discuss the limitations associated with each.- Demonstrate an understanding of the application of artificial intelligence techniques to game playing.- Define the concepts of different planning systems and explain how they differ from classical search techniques.- Obtain a basic understanding of machine learning approaches, neural networks and evolutionary computation.- Distinguish one recommendation approach from another and understand how related research has addressed key problems in this area.

Workload

	Hrs/Semester
Lectures	24
Practical	6
Computer Aided Lab	12
Specified Learning Activities	8
Autonomous Student Learning	50
Total Workload	100

Assessment

	% of Final Grade	Timing
Examination: Written Exam	50	2 hour End of Semester Exam
Multiple Choice Questionnaire: MCQ	15	Varies over the Semester
Practical Examination: Intermediate practical assessments	15	Varies over the Semester
Project: AI Implementation Task	20	Coursework (End of Semester)

Resits

Resit Opportunities

End of Semester Exam

Remediation

If you fail this module you may repeat, resit or substitute where permissible

Dependencies

Module Requisites and Incompatibles

Pre-Requisite :

Required :

Co-Requisite :

Incompatibles :

Additional Information :

Equivalent Modules

Prior Learning

Requirements:

Excluded:

Recommended:

Students should have a good knowledge of Data Structures and Algorithms and reasonable programming skills.

Availability

Timetabling information is displayed only for guidance purposes, relates only to 2010/2011, and is subject to change.

Lectures	Semester 1 Offering 1	Thu: 09:00-09:50 (Sem1: All Weeks)
Lectures	Semester 1 Offering 1	Tue: 09:00-09:50 (Sem1: All Weeks)
Practical	Semester 1 Offering 1	Wed: 10:00-11:50 (Sem1: All Weeks)
Practical	Semester 1 Offering 2	Wed: 12:00-13:50 (Sem1: All Weeks)

Curricular information is subject to change

Last SISWeb sync date: Fri, 16 Sep 2011 20:03:13 +0000

Useful Links

UCD School of Computer Science & Informatics,
University College Dublin,
Belfield, Dublin 4, Ireland

Email:
Tel: +353 1 716 2483
+353 1 716 2469
Fax: +353 1 269 7262

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