Brought to you by EarthWeb
IT Library Logo

Click Here!
Click Here!

Search the site:
 
EXPERT SEARCH -----
Programming Languages
Databases
Security
Web Services
Network Services
Middleware
Components
Operating Systems
User Interfaces
Groupware & Collaboration
Content Management
Productivity Applications
Hardware
Fun & Games

EarthWeb Direct EarthWeb Direct Fatbrain Auctions Support Source Answers

EarthWeb sites
Crossnodes
Datamation
Developer.com
DICE
EarthWeb.com
EarthWeb Direct
ERP Hub
Gamelan
GoCertify.com
HTMLGoodies
Intranet Journal
IT Knowledge
IT Library
JavaGoodies
JARS
JavaScripts.com
open source IT
RoadCoders
Y2K Info

Previous Table of Contents Next


REFERENCES

Fahiem Bacchus. Representing and Reasoning with Probabilistic Knowledge: A Logical
Approach to Probabilities. MIT Press, Cambridge, 1993.
A. Borgida, R.J. Brachman, D.L. McGuinness, and L. Asperin Resnick. Classic: a structural
data model for objects. SIGMOD Record. 18(2):58-67, 1989.
F. Bacchus, A. J. Grove, J. Y. Halpern, and D. Killer. From statistical knowledge bases to
degrees of belief. Artificial Intelligence, 87:75-143, 1996.
B.G. Buchanan and T.M. Mitchell. Model-directed learning of production rules. In D.A.
Waterman and F. Hayes-Roth, Eds., Pattern-Directed Inference Systems, p. 297-312. Academic Press, New York, 1978.
B.G. Buchanan and E.H. Shortliffe, Eds. Rule-Based Expert Systems: The MYCIN Experiments
of the Stanford Heuristic Programming Project. Addison-Wesley, Reading, MA, 1984.
Alan Bundy, F. van Harmelen, C. Horn, and A. Smaill. The Oyster-Clam system. In M.E.
Stickel, Ed., 10th International Conference on Automated Deduction, p. 647-648. Springer-Verlag, 1990. Lecture Notes in Artificial Intelligence No. 449. Also available from Edinburgh as DAI Research Paper 507.
C.W. Churchman and B.G. Buchanan. On the design of inductive systems: some
philosophical problems. Journal for the Philosophy of Science, 20(211): 1969.
K.L. Clark. Negation as failure. In H. Galliere and J. Minker, Eds., Logica and Data
Bases, p. 293-322. Plenum Press, New York, 1978.
E. Charniak and D. McDermott. Introduction to Artificial Intelligence. Addison Wesley,
Reading, MA, 1985.
R. Davis and B.G. Buchanan. Meta-level knowledge: overview and applications. In R. Reddy,
Ed., Proceedings of IJCAI-77, p. 920-927. IJCAI, 1977.
A.P. Dempster. A generalization of bayesian inference. Royal Statistical Society, 30:205-247,
1968.
J. De Kleer. Qualitative and quantitative knowledge in classical mechanics. Ai-tr-352, MIT
AI Laboratory, 1975.
M. Dincbas and J. LePape. Metacontrol of logic programs in metalog. In Elsevier-North
Holland, editor, Proceedings of Fifth-Generation Computer Systems, 1984.
J. Doyle. A truth maintenance system. Artificial Intelligence, 12(3):231-272, 1979.
M. Davis and H. Putnam. A computing procedure for quantification theory. Journal of the ACM,
7(3):201-215, 1960.
C. Elkan. The paradoxical success of fuzzy logic. In Proceedings of the 11th National
Conference of AI, p. 698-703. AAAI Press, 1993.
Edward A. Feigenbaum and Bruce G. Buchanan. Dendral and meta-dendral: roots of
knowledge systems and expert systems applications. Artificial Intelligence, 59:233-240, 1993.
Jean H. Gallier. Logic for Computer Science. John Wiley, 1988.
H. Gerlenter. Realization of a geometry-theorem proving machine. In E.A. Feigenbaum and
J. Feldman, Eds., Computers and Thought, p. 134-152. McGraw-Hill, New York, 1963. (Reprinted from Proceedings of an International Conference on Information Processing, Paris, 1959, UNESCOHouse, 273-282.)
R. Goebel, K. Furukawa, and D.L. Poole. Using definite clauses and integrity constraints
as the basis for a theory formation approach to diagnostic reasoning. In Third International Conference on Logic Programming, p. 211-222, London, England, July 14-18 1986. Imperial College of Science and Technology. Lecture Notes in Computer Science No. , Springer-Verlag.
P. Gilmore. A proof method for quantification theory: its justification and realization. IBM
Journal of Research and Development, 7(3):201-215, 1960.
M.R. Genesereth and N.J. Nilsson. Logical Foundations of Artificial Intelligence. Morgan
Kaufmann, Palo Alto, CA, 1987.
R. Goebel. Exhuming the criticism of the logicist. Computational Intelligence, 4(4):401-404,
1988.
M. Gordon. HOL: A proof generating system for higher-order logic. In G. Birtwistle and P.A.
Subrahmanyam, Eds., VLSI Specification, Verification and Synthesis. Kluwer, 1988.
M.R. Genesereth and D. Smith. Meta-level architecture. memo hpp-81-6, Department of
Computer Science Stanford University, CA, 1981.
P. Hayes. Computation and deduction. In Proceedings of the Second Symposium on
Mathematical Foundations of Computer Science. Czech. Academy of Sciences, 1973.
A.C. Kakas, R.A. Kowalski, and F. Toni. Abductive logic programming. Journal of Logica
and Computation, 2(6):719-770, 1993.
K. Konolige. Abduction versus closure in causal theories. Artificial Intelligence, 27:97-109,
1992.
R. Kowalski. Algorithm = logic + control. Communications of the ACM, 22:424-436, 1979.
R.K. Lindsay, B.G. Buchanan, E.A. Feigenbaum, and J. Lederberg. Applications of Artificial
Intelligence for Chemical Inference: The DENDRAL Project. McGraw-Hill, New York, 1980.
H. Levesque, Ed., Taking issue: Mcdermott's a critique of pure reason. Computational
Intelligence, 3(3), 1987.
D.B. Lenat. AM: an artificial intelligence approach to discovery in mathematics as
heuristic search. In Knowledge-Based Systems in Artificial Intelligence. McGraw Hill, 1982. Also available from Stanford as TechReport AIM 286.
D.B. Lenat and R.V. Guha. Building Large Knowledge-Based Systems: Representation
and Inference in the CYC Project. Addison Wesley, MA, 1990.
J.E. Laird, A. Newell, and P.S. Rosenbloom. Soar: an architecture for general intelligence.
Artificial Intelligence, 33(1):1-64, 1987.
J. McCarthy. Programs with common sense. In Mechanisation of Thought Processes
(Proceedings of a symposium held at the National Physics Laboratory, London, Nov. 1959), p. 77-84, London, 1959. HMSO.
J. McCarthy. Circumscription: a form of non-monotonic reasoning. Artificial Intelligence,
13:27-39, 1980. Also in Readings in Nonmonotonic Reasoning, Ginsberg, M.L., Ed., Morgan Kaufmann, San Mateo, CA, 1987.
D.V. McDermott. A critique of pure reason. Computational Intelligence, 3(3):151-160, 1987.
G. Merziger. Approaches to abductive reasoning -- an overview. Technical Report RR-92-08,
German Research Center for Artificial Intelligence, 1992.
R.S. Michalski. Pattern recognition as rule-guided inductive inference. Transactions on
Pattern Analysis and Machine Intelligence, 2(2-4):349-361, 1980.
Marvin Minsky. Steps towards artificial intelligence. Proceedings of the IRE, 49(1):8-30, 1961.
Marvin Minsky. A framework for representing knowledge. In P.H. Winston, Ed., The
Psychology of Computer Vision, p. 211-277. McGraw Hill, New York, 1975.
T.M. Mitchell. Version Spaces: An Approach to Concept Learning. Ph.D. thesis, Stanford
University, CA, 1978.
S. Muggleton and L. De Raedt. Inductive logic programming: theory and methods.
Journal of Logic Programming, 19&20:629-679, 1994.
S. Muggleton. Inductive Logic
Programming. Academic Press, New York, 1992.
S. Muggleton. Learning from positive data. In Proceedings of the Sixth Inductive Logic
Programming Workshop, p. 225-244, July 14-18 1996. Lecture Notes in Computer Science No. , Springer-Verlag.
A Newell and H. Simon. GPS, a program that simulates human thought. In E. Feigenbaum
and J. Feldman, Eds., Computer and Thought, p. 279-296. McGraw Hill, New York, 1963.
A. Newell and H. Simon. Human Problem Solvings. Prentice hall, New York, 1972.
J. Pearl. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.
Morgan Kaufmann, San Mateo, CA, 1988.
C.S. Peirce. Collected Papers of Charles Sanders Peirce, Vol. 2. Harvard University Press,
1959. Edited by Harston, C. and Weiss, P.
D.L. Poole, Alan K. Mackworth, and Randy Goebel. Computational Intelligence: A Logical
Approach. Oxford University Press, New York, 1997.
D. Poole. A logical framework for default reasoning. Artificial Intelligence, 36:27-47, 1988.
D. Poole. Representing knowledge for logic-based diagnosis. In International Conference
on Fifth Generation Computing Systems, p. 1282-1290, Tokyo, Japan, November 1988.
D.L. Poole. Explanation and prediction. Computational Intelligence, 5(2):97-110, 1989.
D. Poole. Logic programming, abduction and probability: a top-down anytime algorithm
for computing prior and posterior probabilities. New Generation Computing, 11(3-4):377-400, 1993.
D.L. Poole. Probabilistic Horn abduction and Bayesian networks. Artificial Intelligence,
64(1):81-129, 1993.
D.L. Poole. Representing diagnosis knowledge. Annals of Mathematics and Artificial
Intelligence, 11:33-50, 1994.
H.E. Pople. On the mechanization of abductive logic. In Proceedings of the 3rd International
Joint Conference on Artificial Intelligence, p. 147-151, 1973.
E.L. Post. Introduction to a general theory of elementary propositions. American
Journal of Mathematics, 43:163-185, 1921.
D. Prawitz, H. Prawitz, and N. Vogera. A mechanical proof procedure and its realization
in an electronic computer. Journal of the ACM, 7(1&2):102-128, 1960.
J.R. Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo, CA,
1993.
Ray Reiter. A logic for default reasoning. Arcial Intelligence, 13(1-2):81-132, 1980.
J.A. Robinson. A machine-oriented logic based on the resolution principle. Journal of the
ACM, 12(1):23-41, 1965.
R. Schank and R.P. Abelson. Scripts, Plans, Goals, and Understanding. Lawrence Elbaum
Associates, Potomac, MD, 1977.
G. Shafer. A Mathematical Theory of Evidence. Princeton University Press, Princeton, NJ,
1959.
B. Silver. Meta-Level Inference: Representing and Learning Control Information in
Artificial Intelligence. North Holland, 1985.
Alfred Tarski. Logic, Semantics, and Metamathematics. Oxford University Press, 1956.
Jean van Heijenoort. From Frege to Gödel: a Source Book in Mathematical Logice,
1879-1931. Harvard University Press, 1967.
P. Winston. Learning structural descriptions from examples. In P.H. Winston, Ed., The
Psychology of Computer Vision. McGraw Hill, 1975.
Lotfi Zadeh. Fuzzy sets. Information and Control, 8:338-353, 1965.


Previous Table of Contents Next

footer nav
Use of this site is subject certain Terms & Conditions.
Copyright (c) 1996-1999 EarthWeb, Inc.. All rights reserved. Reproduction in whole or in part in any form or medium without express written permission of EarthWeb is prohibited. Please read our privacy policy for details.