@article{turing1950computing,
  author = {Turing, A. M.},
  copyright = {Copyright © 1950 Oxford University Press},
  interhash = {3f7a151a4f79fe75b4bb148b41279a9b},
  intrahash = {c6b8db241dec2cec3477ce771abebb8f},
  issn = {00264423},
  journal = {Mind},
  jstor_articletype = {research-article},
  jstor_formatteddate = {Oct., 1950},
  language = {English},
  number = 236,
  pages = {433--460},
  publisher = {Oxford University Press on behalf of the Mind Association},
  series = {New Series},
  title = {Computing Machinery and Intelligence},
  url = {http://www.jstor.org/stable/2251299},
  volume = 59,
  year = 1950
}

@incollection{forbus1988qualitative,
  abstract = {Qualitative physics is concerned with representing and reasoning about the physical world. The goal of qualitative physics is to capture both the common-sense knowledge of the person on the street and the tacit knowledge underlying the quantitative knowledge used by engineers and scientists. The area is now a little over ten years old, which, at least measured in the span of AI, is a long time. So it makes sense to step back and try to systematize the work in the field and describe the current state of the art.},
  address = {San Francisco, California},
  author = {Forbus, Kenneth D.},
  booktitle = {Exploring Artificial Intelligence},
  chapter = 7,
  interhash = {8733594ffc96474d2c34ce9881ea282d},
  intrahash = {b970bf1995a19b741a1feda04c594d6c},
  pages = {239--296},
  publisher = {Morgan-Kaufmann Publishers, Inc.},
  title = {Qualitative Physics: Past, Present, and Future},
  year = 1988
}

@article{davis1993knowledge,
  abstract = {Although knowledge representation is one of the central and in some ways most familiar concepts in AI, the most fundamental question about it--What is it?--has rarely been answered directly. Numerous papers have lobbied for one or another variety of representation, other papers have argued for various properties a representation should have, while still others have focused on properties that are important to the notion of representation in general.

In this paper we go back to basics to address the question directly. We believe that the answer can best be understood in terms of five important and distinctly different roles that a representation plays, each of which places different and at times conflicting demands on the properties a representation should have.

We argue that keeping in mind all five of these roles provides a usefully broad perspective that sheds light on some longstanding disputes and can invigorate both research and practice in the field. },
  author = {Davis, Randall and Shrobe, Howard and Szolovits, Peter},
  interhash = {0a9d5e8f1265106c18730053f871e80b},
  intrahash = {fc0910c9b3d967f5b01ae73d252d66fb},
  journal = {AI Magazine},
  number = 1,
  pages = {17--33},
  title = {What is a Knowledge Representation},
  url = {http://www.aaai.org/aitopics/assets/PDF/AIMag14-01-002.pdf},
  volume = 14,
  year = 1993
}

@article{shadbolt06semantic,
  abstract = {The original Scientific American article on the Semantic Web appeared in 2001. It described the evolution of a Web that consisted largely of documents for humans to read to one that included data and information for computers to manipulate. The Semantic Web is a Web of actionable information—information derived from data through a semantic theory for interpreting the symbols. This simple idea, however, remains largely unrealized. Shopbots and auction bots abound on the Web, but these are essentially handcrafted for particular tasks; they have little ability to interact with heterogeneous data and information types. Because we haven't yet delivered large-scale, agent-based mediation, some commentators argue that the Semantic Web has failed to deliver. We argue that agents can only flourish when standards are well established and that the Web standards for expressing shared meaning have progressed steadily over the past five years. Furthermore, we see the use of ontologies in the e-science community presaging ultimate success for the Semantic Web—just as the use of HTTP within the CERN particle physics community led to the revolutionary success of the original Web.},
  author = {Shadbolt, Nigel and Berners-Lee, Tim and Hall, Wendy},
  editor = {Staab, Steffen},
  ee = {http://dsonline.computer.org/portal/site/dsonline/menuitem.9ed3d9924aeb0dcd82ccc6716bbe36ec/index.jsp?&pName=dso_level1&path=dsonline/2006/07&file=x3sem.xml&xsl=article.xsl&},
  interhash = {5f95e416982e7d981e2d6daa988180bc},
  intrahash = {ae5cd5e31f0d7847f323a59988fdfab8},
  journal = {IEEE Intelligent Systems},
  number = 3,
  pages = {96-101},
  title = {The Semantic Web Revisited},
  url = {http://eprints.ecs.soton.ac.uk/12614/01/Semantic_Web_Revisted.pdf#search=%22The%20Semantic%20Web%20Revisited%22},
  volume = 21,
  year = 2006
}