Moreover, the undersigned agrees to cooperate in any claim or other action seeking to protect or enforce any right the undersigned has granted to AAAI in the article/paper. The author(s) agree that if anyone brings any claim or action alleging facts that, if true, constitute a breach of any of the foregoing warranties, the author(s) will hold harmless and indemnify AAAI, their grantees, their licensees, and their distributors against any liability, whether under judgment, decree, or compromise, and any legal fees and expenses arising out of that claim or actions, and the undersigned will cooperate fully in any defense AAAI may make to such claim or action.The author(s) warrants that they are the sole author and owner of the copyright in the above article/paper, except for those portions shown to be in quotations that the article/paper is original throughout and that the undersigned right to make the grants set forth above is complete and unencumbered.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.Īuthors who publish with this journal agree to the following terms: 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. In this article, we go back to basics to address the question directly. Numerous papers have lobbied for one or another variety of representation, other papers have argued for various properties a representation should have, and still others have focused on properties that are important to the notion of representation in general.

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.

Knowledge representation in ai