302952 (v.2) Artificial and Machine Intelligence 651

Area:	Department of Computing
Credits:	25.0
Contact Hours:	4.0

The tuition pattern below provides details of the types of classes and their duration. This is to be used as a guide only. For more precise information please check your unit outline.

Workshop:	1 x 4 Hours Weekly
Prerequisite(s):	10225 (v.6) Introduction to Programming Environments 502 or any previous version

Syllabus:	Introduction to LISP, list processing, functional approach. Pattern matching, symbolic representation, LISP - local state, stream processing, function as arguments and results, printing, reading and file manipulation. Search methods, semantic nets and frames in LISP, natural language processing, simple grammar representation. Introduction to neural networks. Introduction to machine learning, constraint propagation, probabilistic reasoning, planning and problem solving paradigms.

To ensure that the most up-to-date information about unit references, texts and outcomes appears, they will be provided in your unit outline prior to commencement.

Field of Education:	020119 Artificial Intelligence
Funding Cluster:	06 - Computing, Built Environment, Health
SOLT (Online) Definitions*:	Not Online *Extent to which this unit or thesis utilises online information
Result Type:	Grade/Mark
Availability
Availability Information has not been provided by the respective School or Area. Prospective students should contact the School or Area listed above for further information.

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