Readings
Readings for Fall, 2002
All members of the class (including auditors) are to read all of the assigned papers and meet in advance of the class in your reading groups to discuss them. The goal is that each group member should contribute her or his own insights and background knowledge to the small group discussions and hopefully clear up many confusions before we get to class. (Or at least, formulate specific questions about any confusions for the class discussion.) Topics that I would like you to cover in your groups include some subset of:
- Does everybody understand the content of the paper? If not, what issues need to be clarified to improve understanding? Does the group have the collective knowledge to answer these questions, or does it require outside input? (E.g., from me, your other classmates, etc.) Feel free to come see me in office hours or to send mail to cs527.
- What claims does the author make and how are those claims substantiated? Do you believe the claims (based on your experience in class, in life, etc.)?
- Is the author addressing real problems for AI or "pseudo-problems"? That is, are the concerns that the author is addressing actually relevant to the AI enterprise in any way, or do they represent some model that's too far removed from reality to be useful?
- How would you extend the author's work and/or suggestions? Do you have specific counterproposals or suggestions, or would you follow up in the directions that the author has already started on? Can you suggest algorithms or techniques (whether from this class or from your other experience) that would be beneficial to the problems that the author is addressing?
Deliverables
Each group should turn in (at the beginning of class) a short (1-2 pages), typewritten summary of their discussion. Specifically, your writeup should include:- A summary of the content of the paper (1-2 paragraphs). Don't simply copy the abstract -- formulate your own summary of the paper. This should be both a description of what questions were addressed, what AI algorithms were used (if any), and the results or conclusions of the study. (Hint: this is good practice at writing your own abstracts, for those who haven't done this much yet.)
- A description of how you would extend/improve this work (1-3 paragraphs). Again, please don't just take the authors' "future work" -- formulate your own thoughts about where to take this work. See the discussion points above for some starting places on this. If you disagree with the author's assessment, feel free to say so, but please offer some alternate directions for this work.
NOTE! If you would like to turn in your writeup electronically, you're welcome to do so. Please email me your summary document in either PDF, PostScript, HTML, or plain ASCII text. Please do not send me MS Word or other proprietary formats. Your submission is still due by the beginning of class (as judged by the time that it arrives in my mailbox).
Finally, I want to encourage you to have fun with these papers. They seem pretty dry, but they're discussing some fascinating aspects of AI as it has been practiced over the last half-century. If you pay attention, you'll learn a lot about where current ideas came from and about how the field has changed over the years.
Enjoy!
The Papers
- Feb 4, 2003
- Minsky, M. Steps Toward Artificial Intelligence Proc. IRE, 49(1), Jan, 1961, pp. 8-30.
- Mar 4, 2003
- Brooks, R. Intelligence Without Representation, Artificial Intelligence Journal (47), 1991, pp. 139-159.
- Apr 1, 2003
- Langley, P. The computational support of scientific discovery. International Journal of Human-Computer Studies, 53, pp 393-410. 2000.
- Apr 24, 2003
- Ginsberg, M., GIB: Steps Toward an Expert-Level Bridge-Playing Program. Proc. Int'l Joint Conf. on AI (IJCAI-99), 1999.
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