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306718 (v.1) Artificial Machine Intelligence 551
Area: | Department of Computing |
Credits: | 25.0 |
Contact Hours: | 3.0 |
Lecture: | 1 x 2 Hours Weekly |
Practical: | 1 x 1 Hours Weekly |
Prerequisite(s): | 5396 (v.7) Software Technology 502 or any previous version
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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. |
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Unit Outcomes: | On the completion of this unit, students should have a basic understanding of the field Artificial Intelligence, its main problems and approaches, be familiar with symbolic representations, search methods, first-order logics and their applications in reasoning and learning tasks as well as be familiar with numerical techniques in AI, including Probabilistic Networks, Neural Networks and their applications. |
Texts and references listed below are for your information only and current as of September 30, 2003. Some units taught offshore are modified at selected locations. Please check with the unit coordinator for up-to-date information and approved offshore variations to unit information before finalising study and textbook purchases. |
Unit References: | G.L. Steele (1990), Common Lisp the Language 2nd ed. Thinking Machines Inc. Digital Press ISBN 1-55558-041-6. H. Abelson, G.J. Sussman and J. Sussman, (1989), Structure and Interpretation of Computer Programs, Addison-Wesley. ISBN: 0-201-08319-1 |
Unit Texts: | S. Russell and P. Norvig, (1995), Artificial Intelligence - A Modern Approach. Prentice Hall ISBN: 0 13 360124 2. P. Winston, P. H, Kaus, H. HORN, H. LISP, 3rd ed. ISBN 0-201-08319-1 |
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Unit Assessment Breakdown: | Assignments (2) 40%, Final Examination 60%. This is by grade/mark assessment. |
Field of Education: | 31300 Electrical and Electronic Engineering and Technology (Narrow Grouping) | HECS Band (if applicable): | 2 |
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Extent to which this unit or thesis utilises online information: | Not Online | Result Type: | Grade/Mark |
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Availability
| Year | Location | Period | Internal | Area External | Central External | | 2004 | Bentley Campus | Semester 1 | Y | | |
Area
External | refers to external course/units run by the School or Department, offered online or through Web CT, or offered by research. |
Central
External | refers to external course/units run through the Curtin Bentley-based Distance Education Area |
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