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Citation format
  1. Harvnb ⇒ Harvtxt
  2. Separate "explanatory notes" from topic-labeled references. Use a "group" parameter and give them their own section.
  3. Add columns to the reference section.
  4. Decide whether (a) everything should use shortened notes, or (b) only the main six (or seven) sources should use shortened notes. Should all the stuff that's used once be moved into the footnotes? There are a couple of cases where this is awkward.
  5. Combine "sub-symbolic" footnotes. Dreyfus, Gladwell, psych. evidence for, etc. Use one footnote for both of these paragraphs.
  6. Artificial brain: should I add the human biology/intelligence footnote into the mix? Should I separate the "thought experiment" from the argument that the brain should be simulated? It seems like there are two topics here but they are a little mixed up right now.
Weak points
  1. Find sources for approaches. Check this out:[1]. The best ones are (1) Marti A. Hearst, Haym Hirsh, "AI's Greatest Trends and Controversies," IEEE Intelligent Systems, vol. 15, no. 1, pp. 8-17, Jan./Feb. 2000, doi:10.1109/5254.820322 and I have pdf, and I have notes on it already. Just work these into citations. (2) Margaret Boden and (3) Marvin Minsky's "Scruffy vs. neat vs. ... ". Define the distinction between sub-symbolic and symbolic AI more clearly. Get a source. Nilsson's textbook is probably the best source.
  2. Mention "combinatorial explosion" in second paragraph of "search and optimization"
  3. Searle is summarized so nicely in "Turing Test" -- could I use this language here?
  4. Could the references in AI winter fill in "Applications of AI"?
  5. Need a section on raw computing power and (maybe intractability). Would love to quote moravec on raw computer power.
Rewrites by other editors
  1. Does "measuring progress" belong under Philosophy? Turing test does. Should this material be added to "Philosophy AI"? At least a link.
Mentioned on talk page.
  1. Write Applications of AI (about a page)
  2. Could use a tiny section on symbolic learning methods, such as explanation based learning, relevance based learning, inductive logic programming, case based reasoning.
  3. Could use a tiny section on knowledge representation tools, like semantic nets, frames, etc.
  4. Control theory could use a little filling out with other tools used for robotics.
  5. Add constraint satisfaction under search. Mention adversarial search.
Additional sources
  1. Take notes on last chapter of Norvig and Russell; apply these to speculation & philosophy sections.
  2. Check that I used the references in User:CharlesGillingham/Notes/Nilsson.

AI Effect[edit]

One the ongoing effects of the AI winter is that funding agencies and investors have the impression that older approaches to AI have failed.[1] While many AI researchers disagree,[2] others have deliberately distanced their work from older approaches, even to the extent of coming up with new names to describe their research, such computational intelligence, cognitive systems, informatics, knowledge-based systems, and so on.


  1. ^
  2. ^