This unit includes history and philosophy of artificial intelligence; intelligent agents; problem solving and search (problem representation, heuristic search, iterative improvement, game playing); knowledge representation and reasoning (extension of material on propositional and first-order logic for artificial intelligence applications, situation calculus, planning, frames and semantic networks); expert systems overview (production systems, certainty factors); reasoning under uncertainty (belief networks compared to other approaches such as fuzzy logic); machine learning (decision trees, neural networks, genetic algorithms).
2 hrs lectures/wk, 1 hr laboratory/wk
The expected weekly workload is 12 hours in total, including:
CSE2309, CSE3309, DGS3691
FIT2004 or CSE2304
Reza Haffari
Consultation hours: Tuesday 2-3pm
Ingrid Zukerman
Consultation hours: Wednesday 3-4pm
Simon Egerton
Tatyana Shmanina
Jessie Phuong Thao Nghiem
| Week | Activities | Assessment |
|---|---|---|
| 0 | No formal assessment or activities are undertaken in week 0 | |
| 1 | Introduction | |
| 2 | Problem solving: search I | |
| 3 | Problem solving: search II | |
| 4 | Game playing and Knowledge representation: propositional logic | |
| 5 | Knowledge representation: first-order logic | |
| 6 | Planning | Assignment 1 due 2 September 2013 |
| 7 | Reasoning under uncertainty: probabilistic reasoning and Bayesian networks | |
| 8 | Reasoning under uncertainty: Statistical learning | |
| 9 | Machine learning | Assignment 2 due 23 September 2013 |
| 10 | Classification and regression | |
| 11 | Markov Decision Processes | |
| 12 | Reinforcement Learning | Assignment 3 due 21 October 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): 60%; In-semester assessment: 40%
| Assessment Task | Value | Due Date |
|---|---|---|
| Assignment 1 - Problem solving: search | 15% | 2 September 2013 |
| Assignment 2 - Knowledge representation and Bayesian networks | 10% | 23 September 2013 |
| Assignment 3 - Machine learning and Markov Decision Processes | 15% | 21 October 2013 |
| Examination 1 | 60% | 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/
Students must demonstrate knowledge of the A* algorithm and other search algorithms, and ability to implement them correctly.
Knowledge of the requisite material. The specific tasks and marking criteria will be distributed at the appropriate time during the semester.
Performance of the program. The specific tasks and marking criteria will be distributed at the appropriate time during the semester.
Recommended texts:
• A Hodges (1992), Alan Turing: The Enigma. London: Vintage.
• P McCorduck (1979), Machines Who Think. Freeman.
• J Haugland (1985), Artificial Intelligence: The Very Idea. MIT.
• M Boden (Ed.) (1990), The Philosophy of AI. Oxford.
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.monash.edu.au/exams/special-consideration.html
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). Please note that it is your responsibility to retain copies of your assessments.
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.
Software: Netica, Weka
Limited copies of prescribed texts are available for you to borrow in the library.
R. Russell and P. Norvig. (2010). Artificial Intelligence: A Modern Approach. (3rd Edition) Prentice Hall.
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Key educational policies include:
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For more information on Monash’s educational strategy, see:
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Previous student feedback has been generally very positive. There is room for improvement in the provision of feedback to students.
If you wish to view how previous students rated this unit, please go to
https://emuapps.monash.edu.au/unitevaluations/index.jsp