weltyc@cs.rpi.edu (Christopher A. Welty) (02/02/89)
Sorry to take so long for this <...insert standard excuses here...>.
These are the refs that so many people asked for on using
KnowledgeCraft, Kee, and so on. It is in Bibtex form, and for the
ease of those using Bibtex I've put all my comments in as tex comments
with lines that begin with %. If you don't use or know bibtex, well
then it's close enough to english that you should be able to figure it
out:
%First, these are the abbreviations I use:
@string{rkrt = "Readings in Knowledge Representation"}
@string{rkrp = "Morgan Kaufman Publishers, Inc."}
@string{rkre = "Ronald J. Brachman and Hector Levesque"}
@string{aaai87 = "Proceeding of AAAI-87: The Sixth National Conference
on Artificial Intelligence, Volume 1"}
@string{aaai82 = "Proceedings of AAAI-82: The National Conference on
Artificial Intelligence"}
% This is one of the first papers on SRL itself, SRL was the language
% that became CRL, which is the language used by Knowledgcraft:
@InCollection{adamd1,
author = "M.S. Fox and J. Wright and D. Adam",
title = "Experiences with SRL: An analysis of a frame-based
knowledge representation",
booktitle = "Expert Database Systems",
publisher = "Benjamin/Cummings",
year = "1985",
editor = "L. Kerschberg",
}
% This paper is an advert for KEE disguised as an overview of Frame
% based systems. It's actually a very good paper on the principles of
% frame-based programming.
@Article{fikesr1,
author = "Richard Fikes and Tom Kehler",
title = "The Role of Frame-Based Representation in Reasoning",
journal = "Communications of the ACM",
year = "1985",
volume = "28",
number = "9",
pages = "904-920",
month = "September",
}
% Another advert for KEE, this more recent paper focuses on Truth
% Maintenance within the KEE environment, and gives good examples on how
% to structure knowledge and do simple reasoning in KEE.
@Article{filmar1,
author = "Robert Filman",
title = "Reasoning With Worlds and Truth Maintenance in a
Knowledge-Based Programming Environment",
journal = "Communications of the ACM",
year = "1988",
volume = "31",
number = "4",
pages = "382-401",
month = "April",
}
% This is a paper on classifiers and integrity (of reasoning) within
% frame systems, focusing on NIKL (KL-ONE) as the representation base.
@TechReport{finint1,
author = "Robert Kass and Ron Katriel and Tim Finin",
title = "Breaking the Primitive Concept Barrier",
institution = "Department of Computer and Information
Science/D2, Moore School of Electrical Engineering,
University of Pennsylvania",
year = "1987",
type = "submitted to IEEE",
number = "CH2408-3/87/0066",
address = "Philadelphia, PA 19104",
}
% I don't think I'm doing too much injustice to others involved when I
% say that Mark Fox was the driving force behind SRL and CRL and hence
% KnowledgeCraft. This is one of his earlier papers on the power of
% inheritance as a form of inference, sorry I don't have a better ref
% than this, I have the paper and I'm really not sure where I got it:
@TechReport{foxm1,
author = "Mark S. Fox",
title = "On Inheritance In Knowledge Representation",
institution = "Department of Computer Science, Carnegie
Mellon University",
year = "1979",
}
% This paper represents probably the best example of using Knowledgcraft
% to model a domain, and more specifically focuses on what Ron Brachman
% calls the `conceptual layer', that is knowledge about time, activity
% and states. This is the best attempt I've seen to formalize a
% conceptual layer, and again is a good example of how to do things in
% KnowledgeCraft (the paper uses CRL, not knowledgecraft specifically):
@Article{foxm2,
author = "Arvind Sathi and Mark S. Fox and Mike Greenberg",
title = "Representation of Activity Knowledge for Project Mangement",
journal = "IEEE Transactions on Pattern Analysis and Machine
Intelligence",
year = "1985",
month = "September",
}
% Another paper by Fox on reasoning, this based on SRL. More ideas on
% how to use inheritance as an inference mechanism:
@InProceedings{foxm3,
author = "Mark S. Fox",
title = "Reasoning with Incomplete Knowledge in a Resource
Limited Environment",
booktitle = "Proceedings of the 7th IJCAI",
year = "1981",
address = "University of British Columbia, Vancouver, BC, Canada",
month = "August",
}
% Although this paper doesn't refer to any explicit system, I've found
% it a useful intro to give people that explains different approaches to
% representing knowledge with semantic networks:
@Article{griffr1,
author = "Robert L. Griffith",
title = "Three Principles of Representation for Semantic Networks",
journal = "ACM Transactions on Database Systems",
year = "1982",
volume = "7",
number = "3",
pages = "417-442",
month = "September",
}
% This is a relatively good survey of KR systems, he looks at ART, KEE,
% KnowledgeCraft, and S.1:
@Article{mettrw1,
author = "William Mettrey",
title = "An Assessment of Tools for Building Large
Knowledge-Based Systems",
journal = "AI Magazine",
year = "1987",
volume = "8",
number = "4",
pages = "81-89",
}
% This paper descibes an implementation of Brachman's KL-ONE system,
% NIKL, which I have found to be the most common implementation in use:
@TechReport{moserm1,
author = "M.G. Moser",
title = "An Overview of NIKL, The New Implementation of KL-ONE",
institution = "Bolt, Beranek and Newman, Inc",
year = "1983",
number = "5421",
}
% These describe yet another KR system, KANDOR, which draws pretty
% heavily on KL-ONE and KRYPTON. KANDOR was used by Fairchild in
% the ARGON project:
@InProceedings{patelp1,
author = "Peter F. Patel-Schneider",
title = "Small can be Beautiful in Knowledge Representation",
booktitle = "Proceedings of the IEEE Workshop on Pronciples of
Knowledge-Based Systems",
year = "1984",
organization = "IEEE",
}
@InProceedings{brachr6,
author = "Peter F. Patel-Schneider and Ronald J. Brachman and
Hector Levesque",
title = "ARGON: Knowledge Rperesentation meets Information Retrieval",
booktitle = "Proceedings of the First Conference on Artificial
Intelligence Applications",
year = "1984",
organization = "IEEE",
}
% I would count these two as the most important background papers on KR
% systems, in which no actual applications are discussed, just a lot of
% theory about what a KR or Frame system should provide (KL-ONE is based
% on these two papers):
@InCollection{woodsw1,
author = "William A. Woods",
title = "What's in a Link: Foundations for Semantic Networks",
booktitle = "Representation and Understanding: Studies in
Cognitive Science",
publisher = "Academic Press",
year = "1975",
editor = "D.G. Bobrow and A.M. Collins",
pages = "35-82",
address = "New York",
}
@Article{brachr11,
author = "Ronald J. Brachman",
title = "What's in a concept: structural foundations for
semantic networks",
journal = "Int. Journal of Man-Machine Studies",
year = "1977",
volume = "9",
pages = "127-152",
}
% And of course the paper on KL-ONE itself:
@Article{brachr2,
author = "Ronald J. Brachman and James G. Schmolze",
title = "An Overview of the KL-ONE Knowledge Representation System",
journal = "Cognitive Science",
year = "1985",
volume = "9",
number = "2",
pages = "171-216",
}
% A description of KRYPTON, which adds considerable assertional power to
% the basic KL-ONE idea:
@InCollection{brachr3,
author = "Ronald J. Brachman and Richard E. Fikes and Hector J.
Levesque",
title = "KRYPTON: A Functional Approach to Knowledge Representation",
booktitle = rkrt,
publisher = rkrp,
year = "1985",
editor = rkre,
chapter = "24",
pages = "411-429",
}
I know that I have used refs to a bunch of others, this was all I
could dig up on short notice (I wasn't expecting so many responses!),
and know that there was some other stuff from ISI and Fairchild on
other implementations of things using NIKL and KANDOR, as well as at
least one other paper on using Knowledgecraft....
I also have a paper that will be finished in a few weeks on general
methodology for using frame systems, I can't guarantee it's of the
caliber of the papers I list here, but it should prove helpful for
people trying to understand these new knowledge engineering tools and
figure out how to approach representing the knowledge...If anyone is
interested let me know.
Christopher Welty --- Asst. Director, RPI CS Labs
weltyc@cs.rpi.edu ...!njin!nyser!weltyc