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FOUNDATIONS OF ARTIFICIAL INTELLIGENCE |
| PHIL 3750 |
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SYLLABUS
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Welcome to the Foundations of AI course, PHIL 3750, for winter term 2010. Materials for the course will accumulate here over the semester.
Term paper topic: Andy Clark's solution to the frame problem.
Describe briefly what a frame problem is (as discussed in class). Then explain how Andy Clark's approach to AI presented in Being there : putting brain, body, and world together again solves (or dismisses or renders meaningless) this problem. You are welcome to use direct quotations from the book, but only to support your argument, not to provide a substitute for it. It is entirely feasible that your essay will fit on 2-3 pages; 5 pages is a maximum (that is, I will not read anything after page 5).
The term paper must be submitted either via email in PDF or in hard copy to 1003 (main office) of CSE Building by midnight April 5.
Recommended Textbooks / Reading (on reserve)
The slides with lectures by Stuart J. Russell are available here or here.
Course Description
This course is designed to introduce Cognitive Science students to Artificial Intelligence (AI) as a framework for modelling and analysing fundamental ideas about the nature of intelligence and cognition. The computer models which AI as proposed may or may not be suitable for explaining human capabilities; perhaps we do things quite differently. But AI serves as a sort of baseline for Cognitive Science. If we do not know of any way to implement some cognitive function in the form of a computer program, then we are not likely to be able to construct a theory within the framework of Cognitive Science to explain how humans do it either.Course Organization and Schedule
The course consists of two parts. In the first half of the term the instructor will present an overview of AI topics in standard lecture form. The second half of the term will be run in a seminar mode with student presentations and discussion on philosophical aspects of AI. The presentations will be based on readings from a list (not exhaustive) provided by the instructor.Grading Criteria / Course Requirements
| Percentage | When | |
| Midterm | 40% | Feb 11 in class |
| Class Presentation or Term Paper | 40% | Feb 23 - April 1 |
| Class Participation | 20% |
The midterm will cover the material presented in lectures and will take place in class around mid-February.
Class presentation (on one of the topics listed below) will be done by two students. It will cover at least the papers specified on the reading list related to that topic.
The term paper (3-5 pages) will be on the topic specified later by the instructor. The topic will refer directly to the content of Andy Clark's book Being There.
The students may choose between a class presentation and the term paper.
Class participation is understood as active participation in discussion, and not only class attendance. Everone is expected to read all papers assigned for each class.
Lecture and Presentation/Reading Schedule (subject to change)
| Date | Topic | Presenters |
| Jan 5 | Intro | |
| Jan 7 | Chapter 1 | |
| Jan 12 | Chapter 2 | |
| Jan 14 | Chapter 7 | |
| Jan 19 | Chapter 7 (cont.) | |
| Jan 21 | Chapter 18 | |
| Jan 26 | Chapter 22 | |
| Jan 28 | Non-monotonic reasoning. | |
| Feb 2 | Intractability | |
| Feb 4 | Godel's Theorem | |
| Feb 9 | Computer Vision | Anna Topol (guest lecture) |
| Feb 11 | Midterm | |
| Feb 15-19 | Break | |
| Feb 23 | Emergence: background | TBA |
| Feb 25 | Emergence: consciousness | TBA |
| Mar 2 | Godel's Theorem | Adam Shubinsky |
| Mar 4 | Chinese Room | Mark Zolotar |
| Mar 9 | The Frame Problem (1) | Steve Lovasz and Chris Turner |
| Mar 11 | The Frame Problem (2) | Meem Siddique |
| Mar 16 | No class | |
| Mar 18 | Embodied AI | Srishti Nayak |
| Mar 23 | Neural Networks and Connectionism | Jonathan Mikkila |
| Mar 25 | Innateness | Dmitriy Semenov and Peter Verveniotis |
| Mar 30 | Robots and Ethics | Cuong Nguyen |
| Apr 1 | AI and the Humanities | TBA |
Academic Integrity / Honesty / Plagiarism
See York University's Policy on Academic Honesty.
Plagiarism is defined as taking the language, ideas, or thoughts of another, and representing them as your own. If you use someone else's ideas, cite them. If you use someone else's words, clearly mark them as a quotation. All instances of plagiarism will be reported.
These policies are not intended to keep students from working with other students. One can learn much working with other, so this is to be encouraged. Should you encounter any situations for which you are uncertain whether such collaboration is permitted or not, please ask.
Readings
Books and Collections (the ones with * are available on reserve)1. M. Bedau and P. Humphreys (eds.), Emergence, MIT Press 2008 *
2. R. Cummins and D.D. Cummins (eds.), Minds, Brains and Computers *
3. R. Penrose, The Emperor's New Mind *
4. R. Penrose, Shadows of the Mind
5. J.R. Newman and E. Nagel, Godel's Proof
6. Michael R. Garey and David S. Johnson, Computers and Intractabilty. A guide to the Theory of NP-Completeness
7. W. Bechtel and G. Graham (eds.), A Companion to Cognitive Science *
8. Thinking about android epistemology, edited by Kenneth M. Ford, Clark Glymour, & Patrick J. Hayes. *
9. S. Franchi and G. Guzeldere (eds.) Mechanical Bodies, Computational Minds. *
10. R, Pfeifer and C. Scheier, Understanding Intelligence *
11. Z. Pylyshyn, The Robot's Dilemma. The Frame Problem in AI *
12. J. Copeland, Artificial Intelligence. A Philosophical Introduction.