Course Profile Print View: COMP7702 - Sem 2 2009 - St Lucia - Internal

COMP7702 - Sem 2 2009 - St Lucia - Internal

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1. General Course Information

1.1 Course Details

Course Code: COMP7702 Course Title: Artificial Intelligence
Coordinating Unit: School of Information Technology and Electrical Engineering
Semester: Semester 2, 2009 Mode: Internal
Level: Postgraduate Coursework
Location: St Lucia
Number of Units: 2 Contact Hours Per Week: 2L2T
Pre-Requisites: CSSE7030
Recommended Pre-Requisites: CSSE7023 + COMP7505
Incompatible: COMP3701 or COMP3702 or COMP7701

Course Description: Methods & techniques within the field of artificial intelligenceI, including problem solving and optimisation by search, representing and reasoning with uncertain knowledge and machine learning. Specific emphasis on the practical utility of algorithms and their implementation in software.

Assumed Background: The course assumes students have the ability to create computer programs using a high-level programming language. Students should also have some knowledge of abstract data structures, their use in programs, and the formulation of appropriate algorithms which use them.

1.2 Course Introduction

Methods and techniques within the field of artificial intelligence solve problems - both theoretical and practical. The course aims to provide the student with a broad understanding of the field of Artificial Intelligence. The course describes several of the most important algorithms and techniques that have found theoretical and practical applicability. The course enables the student

to gain an appreciation for the scientific context of artificial intelligence,
to understand and develop computing algorithms, and to analyse their properties,
to find the right tools for solving specific problems, and to implement such tools in software.

1.3 Course Staff

Course Coordinator: Dr Ruth Schulz
Phone: 3365 9765 Email: ruth@itee.uq.edu.au
Campus: St Lucia Building: Axon Building (Map) Room: 308
Consultation: See the course web site for consultation times.

1.4 Timetable

Timetables are available on mySI-net.

2. Aims, Objectives & Graduate Attributes

2.1 Course Aims

In general terms, it is expected that the student gains an understanding of the theories, methods and practices which form the basis of Artificial Intelligence. The course aims to introduce the basic concepts and methods used in the field of artificial intelligence and provide students with skills in the application of these techniques. Specifically the course aims to give students an overview of the following topics in artificial intelligence:

Problem solving and optimisation (search algorithms)
Reasoning with uncertain knowledge (probability theory)
Machine Learning (decision trees, neural networks, etc)
Probabilistic approaches for information retrieval

2.2 Learning Objectives

After successfully completing this course you should be able to:

1  understand and apply the theories, methods and practices which form the basis of artificial intelligence
2  understand that artificial intelligence may be approached at various levels of detail, and through various theoretical frameworks (computing algorithms, logic, probability theory, etc)
3  appreciate that computer science, mathematics and statistics, engineering, philosophy, neuroscience and psychology have had an influence on the field of artificial intelligence
4  master a wide range of subjects relating to artificial intelligence from a large collection of sources, and show evidence of such knowledge in both written and practical work
5  effectively solve problems relating to topics discussed in class and in the literature in groups of fellow students
6  develop an in-depth understanding of search algorithms and machine learning techniques, and their implementations
7  develop an ability to critically read text material and extract useful knowledge applicable to the specific course contents, as well as finding effective solutions to open-ended problems
8  incorporate artificial intelligence into software (prompting many design and technical decisions)
9  appreciate philosophical questions raised in relation to the design, construction and use of artificial intelligence

2.3. Graduate Attributes

Successfully completing this course will contribute to the recognition of your attainment of the following UQ (Postgrad Coursework) graduate attributes:

GRADUATE ATTRIBUTE	LEARNING OBJECTIVES
*A. IN-DEPTH KNOWLEDGE OF THE FIELD OF STUDY*
A2. A broad understanding of the field of study, including how other disciplines relate to the field of study.	1, 3, 4
A3. A comprehensive and in-depth knowledge in the field of study.	1, 6
A5. An international perspective on the field of study.
A7. An appreciation of the link between theory and practice.	1, 8
*B. EFFECTIVE COMMUNICATION*
B1. The ability to collect, analyse and organise information and ideas and to convey those ideas clearly and fluently, in both written and spoken forms.	1, 4, 7, 8
B2. The ability to interact effectively with others in order to work towards a common outcome.	5
B3. The ability to select and use the appropriate level, style and means of communication.
B4. The ability to engage effectively and appropriately with information and communication technologies.	6, 8
B5. The ability to practise as part of an interdisciplinary team.	5
*C. INDEPENDENCE AND CREATIVITY*
C2. The ability to work and learn independently and effectively.
C3. The ability to generate ideas and adapt innovatively to changing environments.	7
C5. The ability to formulate and investigate problems, create solutions, innovate and improve current practices.
C6. The abilities and skills that provide a foundation for future leadership roles.
*D. CRITICAL JUDGEMENT*
D2. The ability to apply critical reasoning to issues through independent thought and informed judgement.	7, 8
D4. The ability to process material and to critically analyse and integrate information from a wide range of sources.	5
D5. The ability to evaluate opinions, make decisions and to reflect critically on the justifications for decisions using an evidence-based approach.
*E. ETHICAL AND SOCIAL UNDERSTANDING*
E1. An understanding of social and civic responsibility.
E3. An appreciation of the philosophical and social contexts of a discipline.	2, 9
E4. A knowledge and respect of ethics and ethical standards in relation to a major area of study.
E5. A knowledge of other cultures and times and an appreciation of cultural diversity.
E7. The ability to work effectively and sensitively across all areas of society.
E8. An understanding of and respect for the roles and expertise of associated disciplines.	4

3. Learning Resources

3.1 Required Resources

The course web page will contain lecture notes, tutorials and assignment specification.

3.2 Recommended Resources

Russell S. and Norvig P., Artificial Intelligence: A modern approach, 2^nd ed., 2003.

3.3 University Learning Resources

Access to required and recommended resources, plus past central exam papers, is available at the UQ Library website (http://library.uq.edu.au/search/r?SEARCH=COMP7702).

The University offers a range of resources and services to support student learning. Details are available on the myServices website (https://student.my.uq.edu.au/).

3.4 School of Information Technology and Electrical Engineering Learning Resources

Students enrolled at St Lucia who wish to retain a hard copy of this profile can use the free print quota provided each semester to students enrolled in courses in the School of Information Technology & Electrical Engineering. For information on how to use this print quota, see the School Policy on Student Photocopying and Printing (St Lucia) (http://www.itee.uq.edu.au/about_ITEE/policies/copy-print.html).

ITEE course websites can be found at http://www.itee.uq.edu.au/~COURSECODE. Many ITEE courses also have Usenet newsgroups, named uq.itee.COURSECODE. Instructions for accessing newsgroups are available at http://studenthelp.itee.uq.edu.au/faq/1stYearFAQ.html#accessnews.

4. Teaching & Learning Activities

4.1 Learning Activities

4.2 Other Teaching and Learning Activities Information

You are not required to attend all of the teaching sessions, but you are strongly encouraged to do so. The lectures and tutorials have been specifically designed to aid your learning of the course material. Failure to attend a session may result in you being seriously disadvantaged. Note that active participation in tutorials requires your attendance.

5. Assessment

5.1 Assessment Summary

This is a summary of the assessment in the course. For detailed information on each assessment, see 5.5 Assessment Detail below.

Assessment Task	Due Date	Weighting	Learning Objectives
Tutorial Exercise Tutorial active participation	3 Aug 09 - 30 Oct 09	10%	4, 5, 6, 7
Exam - Mid Semester During Class Mid-semester	1 Sep 09 14:00 - 1 Sep 09 15:50	10%	1, 2, 3, 4, 6, 7, 9
Project Assignment 1	11 Sep 09 17:00	10%	5, 6, 7, 8
Project Assignment 2	23 Oct 09 17:00	20%	4, 5, 6, 7, 8
Exam - during Exam Period (Central) Final examination	Examination Period	50%	1, 2, 3, 4, 9

5.2 Course Grading

Grade 1, Fail: Fails to demonstrate most or all of the basic requirements of the course: Requires a total mark of 1 or above.

The minimum percentage required for a grade of 1 is: 0%

Grade 2, Fail: Demonstrates clear deficiencies in understanding and applying fundamental concepts; communicates information or ideas in ways that are frequently incomplete or confusing and give little attention to the conventions of the discipline: Requires a total mark of 20 or above.

Grade 3, Fail: Demonstrates superficial or partial or faulty understanding of the fundamental concepts of the field of study and limited ability to apply these concepts; presents undeveloped or inappropriate or unsupported arguments; communicates information or ideas with lack of clarity and inconsistent adherence to the conventions of the discipline: Requires a total mark of 45 or above.

Grade 4, Pass: Demonstrates adequate understanding and application of the fundamental concepts of the field of study; develops routine arguments or decisions and provides acceptable justification; communicates information and ideas adequately in terms of the conventions of the discipline: Requires a total mark of 50 or above.

Grade 5, Credit: Demonstrates substantial understanding of fundamental concepts of the field of study and ability to apply these concepts in a variety of contexts; develops or adapts convincing arguments and provides coherent justification; communicates information and ideas clearly and fluently in terms of the conventions of the discipline: Requires a total mark of 65 or above.

Grade 6, Distinction: As for 5, with frequent evidence of originality in defining and analysing issues or problems and in creating solutions; uses a level, style and means of communication appropriate to the discipline and the audience: Requires a total mark of 75 or above.

Grade 7, High Distinction: As for 6, with consistent evidence of substantial originality and insight in identifying, generating and communicating competing arguments, perspectives or problem solving approaches; critically evaluates problems, their solutions and implications: Requires a total mark of 85 or above.

5.3 Late Submission

No extensions will be granted except in exceptional personal circumstances (documented medical reason or family emergency). Personal hardware or computer failures are not grounds for extension. Requests for extensions must be done in a timely manner, at least within one week of the time of expected delivery.

5.5 Assessment Detail

Tutorial active participation

Type: Tutorial Exercise
Learning Objectives Assessed: 4, 5, 6, 7
Due Date:
3 Aug 09 - 30 Oct 09
Weight: 10%
Task Description:

Tutorials are intended to reinforce and support material discussed in lectures. Active participation in tutorials contributes 10% towards the final grade. Active participation rather than attendance will be assessed during tutorials. Students are expected to complete exercises, take part in discussions and submit tutorial work. Of the 12 scheduled tutorials, 10 have exercises (each worth 1 mark). The remaining two tutorials are used to support assignments (which are assessed as specified separately).

Criteria & Marking: Tutorial answers need to be submitted each week and will be marked based on completeness and accuracy.
Submission: Submitted in written form to the tutor after each tutorial (no later than 48 hours after).

Mid-semester

Type: Exam - Mid Semester During Class
Learning Objectives Assessed: 1, 2, 3, 4, 6, 7, 9
Due Date:
1 Sep 09 14:00 - 1 Sep 09 15:50
Weight: 10%
Perusal: 5 minutes
Duration: 50 minutes
Format: Multiple-choice
Task Description: The exam will be in-class. A 2B pencil will be required.
Criteria & Marking: Multiple choice questions will be given one mark for each correct answer. No marks will be deducted for wrong answers.

Assignment 1

Type: Project
Learning Objectives Assessed: 5, 6, 7, 8
Due Date:
11 Sep 09 17:00
Weight: 10%
Task Description:

The assignment prompts the student to understand search algorithms to solve practical problems. The assignment asks the student to implement the solution as a computer program. The solution is reported in written form. The assignment can only be completed in pairs or individually.

The assignment specification is available from the course web page at least three weeks before the deadline.

Criteria & Marking: Both code and report will be marked for accuracy and completeness.
Submission: Use online assignment submission system to submit both a report and program code.

Assignment 2

Type: Project
Learning Objectives Assessed: 4, 5, 6, 7, 8
Due Date:
23 Oct 09 17:00
Weight: 20%
Task Description:

The assignment prompts the student to understand machine learning algorithms and methodology. It asks the student to implement a solution as a computer program. The assignment is reported in written form. The assignment can only be completed in pairs or individually.

The assignment specification is available from the course web page at least three weeks before the deadline.

Criteria & Marking: Both code and report will be marked for accuracy and completeness.
Submission: Use the online assignment submission system to submit both a report and program code.

Final examination

Type: Exam - during Exam Period (Central)
Learning Objectives Assessed: 1, 2, 3, 4, 9
Due Date:
Examination Period
Weight: 50%
Perusal: 10 minutes
Duration: 120 minutes
Format: Multiple-choice, Short answer, Short essay, Problem solving
Task Description:

A two hour final examination will be held during the final examination period. The examination will be closed-book and will contain both multiple-choice and short-answer questions. You should also bring a battery-operated non-programmable calculator. Programmable calculators and other computing or communication devices are NOT permitted. You will require a HB or 2B pencil and an eraser to complete the exam.

The examination paper aims to test

familiarity with the historical context of artificial intelligence
knowledge of several definitions of artificial intelligence
an understanding of problem solving and optimisation techniques based on search (both uninformed and informed)
knowledge of declarative representation and reasoning
familiarity with logic programming
understanding of general principles in the area of machine learning
knowledge of machine learning techniques (including decision tree learning and neural networks)
an understanding of probability theory and how it can be applied in represention and reasoning with uncertain knowledge, and in machine learning techniques

In addition to the requirements of the COMP3702 course, the COMP7702 final examination also tests the students ability to synthesise knowledge of artificial intelligence at a postgraduate level by including one or more questions of a short-essay type.
Criteria & Marking: Multiple choice questions will be given one mark for each correct answer. No marks will be deducted for wrong answers.

Short answer, short essay, and problem solving questions will be marked for completeness and accuracy.

6. Policies & Guidelines

This section contains the details of and links to the most relevant policies and course guidelines. For further details on University Policies please visit myAdvisor and the University Handbook of Policies and Procedures.

6.1 Assessment Related Policies and Guidelines

University Policies & Guidelines

An overview of the University’s assessment-related policies can be found on myAdvisor (http://www.uq.edu.au/myadvisor/index.html?page=2910).

Academic Integrity
It is the University's task to encourage ethical scholarship and to inform students and staff about the institutional standards of academic behaviour expected of them in learning, teaching and research. Students have a responsibility to maintain the highest standards of academic integrity in their work. Students must not cheat in examinations or other forms of assessment and must ensure they do not plagiarise.

Plagiarism
The University has adopted the following definition of plagiarism:

Plagiarism is the act of misrepresenting as one's own original work the ideas, interpretations, words or creative works of another. These include published and unpublished documents, designs, music, sounds, images, photographs, computer codes and ideas gained through working in a group. These ideas, interpretations, words or works may be found in print and/or electronic media.

Students are encouraged to read the UQ Academic Integrity and Plagiarism policy (http://www.uq.edu.au/hupp/index.html?page=25128) which makes a comprehensive statement about the University's approach to plagiarism, including the approved use of plagiarism detection software, the consequences of plagiarism and the principles associated with preventing plagiarism.

Feedback on Assessment
Feedback is essential to effective learning and students can expect to receive appropriate and timely feedback on all assessment. For a detailed explanation of the feedback you are entitled to, you should consult the policy on Student Access to Feedback on Assessment. (http://www.uq.edu.au/hupp/index.html?page=25109)

As a student you have a responsibility to incorporate feedback into your learning; make use of the assessment criteria that you are given; be aware of the rules, policies and other documents related to assessment; and provide teachers with feedback on their assessment practices.

There are certain steps you can take if you feel your result does not reflect your performance. Please refer to the myAdvisor web site. (http://www.uq.edu.au/myadvisor/index.html?page=2953)

School of Information Technology and Electrical Engineering Assessment Guidelines

Misconduct

Further to the statement on academic integrity and plagiarism above, students are required to read and understand the ITEE policy on Student Misconduct (http://www.itee.uq.edu.au/about_ITEE/policies/student-misconduct.html).

Late Arrival or Non-attendance at Examinations

The policy and procedure for late arrival or non-attendance at centrally controlled and school-based examinations is set out in the University's Assessment policy (HUPP 3.30.1), section 4.8 at http://www.uq.edu.au/hupp/index.html?page=25109.

In the case that a student requests a special exam for a School-controlled exam, the request will be considered and, if allowed, the timing shall be determined by the course coordinator, in consultation with the School's Chief Examiner where necessary, and in accordance with HUPP 3.30.1. Unless otherwise indicated in the Course Profile, applications must be made in writing to the Head of School no later than 5 days after the exam. Late applications will not be accepted.

Examination Feedback

In addition to the advice above, students wishing to view examination answer scripts and/or question papers should consult with the School office (Room 217, General Purpose South Building [78], St Lucia) regarding arrangements. The ITEE policy on exam script viewing is available at http://study.itee.uq.edu.au/current_students/exam_script_viewing.html.

Supplementary Assessment

If you fail this course you may be eligible for supplementary assessment - see the general award rules and/or your program rules for details. You should note that even though you may be eligible for supplementary assessment under these rules, in some circumstances there may be no practical assessment that can be offered to allow you to meet the minimum passing requirements. These circumstances may include failure based on:

group or team based assessment;
attendance or class participation requirements;
laboratory-based assessment, where laboratories can't practically be made available after classes have finished;
project or thesis-based assessment, where a significant period of time would be required to undertake supplementary assessment;
progressive assessment, where subsequent assessment items build on earlier assessment items; or
multiple assessment items, where it is impractical to offer multiple supplementary assessment items.

If the course coordinator determines that there is no practical supplementary assessment that can be offered to allow you to improve your grade, then you will not be offered supplementary assessment and your grade will remain unchanged.

Calculators in Examinations

Some examinations in the School of Information Technology and Electrical Engineering restrict the type of calculator that can be used. If this course profile does not specify any calculator restrictions, you should check with the course coordinator as to whether any restrictions apply. In some examinations, you may only be permitted to use an EPSA/EAIT approved and labelled non-programmable calculator. It is your responsibility to ensure you have a suitable approved and labelled calculator if required.

6.2 Other Policies and Guidelines

University Policies and Guidelines

Placement Courses
Students on a placement course – also known as a work placement, internship, industry study, industry experience, clinical practice, clinical placement, practical work, practicum, fieldwork, teaching practice – should refer to the University policy, Placement Courses (http://www.uq.edu.au/hupp/index.html?page=25120) for detailed information.

Working with Children
Students whose studies include a professional/work placement, internship, clinical practice, teaching practice or other similar activity which involves them in regular contact with children should refer to the University policy, Working with Children Check - "blue card" (http://www.uq.edu.au/hupp/index.html?page=25004) to find out how to apply for a ‘blue card’.

Students with a Disability
Any student with a disability who may require alternative academic arrangements, including assessment, in the course/program is encouraged to seek advice at the commencement of the semester from a Disability Adviser at Student Support Services. Refer to the University policy, Students with a Disability (Disability Action Plan) (http://www.uq.edu.au/hupp/index.html?page=25122) and to the policy on Special Arrangements for Examinations for Students with a Disability (http://www.uq.edu.au/hupp/index.html?page=25111

Where an adjustment is made to an accredited program, it is the responsibility of the relevant Faculty to liaise with professional and registration bodies regarding the acceptability of the change/s.

Occupational Health and Safety
Undergraduate Students (http://www.uq.edu.au/hupp/index.html?page=25055) and Postgraduate Students (http://www.uq.edu.au/hupp/index.html?page=25057) should be familiar with the University policies on occupational health and safety in the laboratory.

Other School of Information Technology and Electrical Engineering Guidelines

Ethical Clearance

If your course involves assignment or project work involving human subjects or human-related materials, you must investigate the need for ethical clearance and obtain it when required. Information on ethical clearance can be found at http://www.uq.edu.au/research/orps/index.html?page=5064&pid=5256.

Learning Summary

Below is a table showing the relationship between the learning objectives for this course and the broader graduate attributes developed, the learning activities used to develop each objective and the assessment task used to assess each objective.

Learning Objectives

After successfully completing this course you should be able to:

Assessment & Learning Activities

	Learning Objectives
	1	2	3	4	5	6	7	8	9
Learning Activities
Lectures (Lecture Series)
Tutorials (Tutorial Series)
Assessment Tasks
Tutorial active participation
Mid-semester
Assignment 1
Assignment 2
Final examination

Graduate Attributes

Successfully completing this course will contribute to the recognition of your attainment of the following UQ (Postgrad Coursework) graduate attributes:

	Learning Objectives
	1	2	3	4	5	6	7	8	9
Graduate Attributes
*A IN-DEPTH KNOWLEDGE OF THE FIELD OF STUDY*
A2. A broad understanding of the field of study, including how other disciplines relate to the field of study.
A3. A comprehensive and in-depth knowledge in the field of study.
A5. An international perspective on the field of study.
A7. An appreciation of the link between theory and practice.
*B EFFECTIVE COMMUNICATION*
B1. The ability to collect, analyse and organise information and ideas and to convey those ideas clearly and fluently, in both written and spoken forms.
B2. The ability to interact effectively with others in order to work towards a common outcome.
B3. The ability to select and use the appropriate level, style and means of communication.
B4. The ability to engage effectively and appropriately with information and communication technologies.
B5. The ability to practise as part of an interdisciplinary team.
*C INDEPENDENCE AND CREATIVITY*
C2. The ability to work and learn independently and effectively.
C3. The ability to generate ideas and adapt innovatively to changing environments.
C5. The ability to formulate and investigate problems, create solutions, innovate and improve current practices.
C6. The abilities and skills that provide a foundation for future leadership roles.
*D CRITICAL JUDGEMENT*
D2. The ability to apply critical reasoning to issues through independent thought and informed judgement.
D4. The ability to process material and to critically analyse and integrate information from a wide range of sources.
D5. The ability to evaluate opinions, make decisions and to reflect critically on the justifications for decisions using an evidence-based approach.
*E ETHICAL AND SOCIAL UNDERSTANDING*
E1. An understanding of social and civic responsibility.
E3. An appreciation of the philosophical and social contexts of a discipline.
E4. A knowledge and respect of ethics and ethical standards in relation to a major area of study.
E5. A knowledge of other cultures and times and an appreciation of cultural diversity.
E7. The ability to work effectively and sensitively across all areas of society.
E8. An understanding of and respect for the roles and expertise of associated disciplines.