This is the foundation unit for the Intelligent Systems specialisation. It introduces the main problems and approaches to designing intelligent software systems including automated search methods, reasoning under uncertainty, planning, software agents, recommender systems, machine learning paradigms, natural language processing, user modelling and evolutionary algorithms.
2 hrs lectures/wk, 2 hrs laboratories/wk
For on-campus students, workload commitments per week are:
Students are expected to work 12 hours per week.
CSE5610
Mark Carman
| Week | Activities | Assessment |
|---|---|---|
| 0 | No formal assessment or activities are undertaken in week 0 | |
| 1 | Introduction | |
| 2 | Problem Solving | |
| 3 | Knowledge Representation | |
| 4 | Planning | Assignment 1 due 28 March 2013 |
| 5 | Soft Computing | |
| 6 | Evolutionary Algorithms | |
| 7 | Bayesian Networks | |
| 8 | Intelligent Decision Support | Assignment 2 due 3 May 2013 |
| 9 | Supervised Machine Learning | |
| 10 | Unsupervised Machine Learning | |
| 11 | Agent-Based Modeling | |
| 12 | Stochastic Problem Solving | Assignment 3 due 31 May 2013 |
| SWOT VAC | No formal assessment is undertaken in SWOT VAC | |
| Examination period | LINK to Assessment Policy: http://policy.monash.edu.au/policy-bank/ academic/education/assessment/ assessment-in-coursework-policy.html |
*Unit Schedule details will be maintained and communicated to you via your learning system.
Examination (3 hours): 70%; In-semester assessment: 30%
| Assessment Task | Value | Due Date |
|---|---|---|
| Assignment 1 - Knowledge Representation and Planning | 10% | 28 March 2013 |
| Assignment 2 - Bayesian Networks and Soft Computing | 10% | 3 May 2013 |
| Assignment 3 - Machine Learning | 10% | 31 May 2013 |
| Examination 1 | 70% | To be advised |
Faculty Policy - Unit Assessment Hurdles (http://www.infotech.monash.edu.au/resources/staff/edgov/policies/assessment-examinations/unit-assessment-hurdles.html)
Academic Integrity - Please see the Demystifying Citing and Referencing tutorial at http://lib.monash.edu/tutorials/citing/
Correctness and completeness of answers to problems.
Correctness and completeness of submitted answers and/or Bayesian networks.
Correctness and completeness of answers to machine learning problems.
Monash Library Unit Reading List
http://readinglists.lib.monash.edu/index.html
Submission must be made by the due date otherwise penalties will be enforced.
You must negotiate any extensions formally with your campus unit leader via the in-semester special consideration process: http://www.infotech.monash.edu.au/resources/student/equity/special-consideration.html.
No resubmissions.
See Library Guides for Citing and Referencing athttp://guides.lib.monash.edu/content.php?pid=88267&sid=656564
It is a University requirement (http://www.policy.monash.edu/policy-bank/academic/education/conduct/plagiarism-procedures.html) for students to submit an assignment coversheet for each assessment item. Faculty Assignment coversheets can be found at http://www.infotech.monash.edu.au/resources/student/forms/. Please check with your Lecturer on the submission method for your assignment coversheet (e.g. attach a file to the online assignment submission, hand-in a hard copy, or use an online quiz).
If Electronic Submission has been approved for your unit, please submit your work via the learning system for this unit, which you can access via links in the my.monash portal.
Please check with your lecturer before purchasing any Required Resources. Limited copies of prescribed texts are available for you to borrow in the library, and prescribed software is available in student labs.
Netica (free)
Netlogo (free)
Weka Data Mining Toolkit (free)
Web access
Limited copies of prescribed texts are available for you to borrow in the library.
Russell, S and Norvig, P. (2010). Artificial Intelligence - A Modern Approach. (3rd Edition) Prentice-Hall.
Witten, I and Frank, E. (2005). Data Mining - Practical Machine Learning Tools and Techniques. (3rd Edition) Elsevier.
Korb, K and Nicholson, A. (2010). Bayesian Artificial Intelligence. (2nd Edition) CRC Press.
Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and to provide advice on how they might uphold them. You can find Monash’s Education Policies at: www.policy.monash.edu.au/policy-bank/academic/education/index.html
Key educational policies include:
The University provides many different kinds of support services for you. Contact your tutor if you need advice and see the range of services available at http://www.monash.edu.au/students. For Sunway see http://www.monash.edu.my/Student-services, and for South Africa see http://www.monash.ac.za/current/.
The Monash University Library provides a range of services, resources and programs that enable you to save time and be more effective in your learning and research. Go to www.lib.monash.edu.au or the library tab in my.monash portal for more information. At Sunway, visit the Library and Learning Commons at http://www.lib.monash.edu.my/. At South Africa visit http://www.lib.monash.ac.za/.
For more information on Monash’s educational strategy, see:
www.monash.edu.au/about/monash-directions and on student evaluations, see: www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html
Assessment weighting has been changed due to students' feedback.
If you wish to view how previous students rated this unit, please go to
https://emuapps.monash.edu.au/unitevaluations/index.jsp