Registry

Module Specifications

Current Academic Year 2009 - 2010
This information is provisional and subject to change.

Module Title	Introduction to Artificial Intelligence
Module Code	CA300
School	Computing
Online Module Resources
Module Co-ordinator	Dr Mark Humphrys	Office Number	L2.25
Level	3	Credit Rating	5
Pre-requisite	None
Co-requisite	None

Module Aims

To introduce students to the definition of Artificial Intelligence (AI), debates in the Philosophy of Mind, the prospects of AI, what defines AI as distinct from other parts of Computer Science, and some basic algorithms in search, learning and evolution. To implement these ideas in a competitive internet-based project (in any programming language - though some tools are provided for Java).

Learning Outcomes

7 Students will be familiar with the philosophical and historical contect of AI. 7 Students will be familiar with debates on the relationship of AI to cognitive science. 7 Students will understand the concept of solution spaces that are too large to be exhaustively explored, and the concept of heuristic exploration of such a space. 7 Students will have experience programming such a system. 7 Students will be familiar with some basic algorithms for machine learning and machine evolution.

Indicative Time Allowances
	Hours
Lectures	24
Tutorials	0
Laboratories	12
Seminars	0
Independent Learning Time	39

Total	75
Placements
Assignments

NOTE

Assume that a 5 credit module load represents approximately 75 hours' work, which includes all teaching, in-course assignments, laboratory work or other specialised training and an estimated private learning time associated with the module.

Indicative Syllabus

· Philosophy of AI. · History of AI. · Machine Learning. · Neural Networks, Back-propagation. · Other forms of learning. · Machine Evolution. · Genetic Algorithms. · Other forms of evolution. · Summary - Solution spaces, heuristic search, learning and evolution. · Architectures of autonomous agents. · The World-Wide-Mind (Porject).

Assessment
Continuous Assessment	30%	Examination Weight	70%

Indicative Reading List

Essential Artificial Intelligence: Structures and strategies for complex problem solving, Luger, G. F. & Stubblefield, W. A. Supplementary Rich, E. & Knight, K. , Artificial Intelligence, Thornton, C. J. , Artificial Intelligence through search.

Programme or List of Programmes

BSSA

Study Abroad (DCU Business School)

BSSAO

Study Abroad (DCU Business School)

CAIS

BSc in Computer Applications (Inf.Sys.)

CASE

BSc in Computer Applications (Sft.Eng.)

ECSA

Study Abroad (Engineering & Computing)

ECSAO