AI Languages and Processing
Sanja J. Vranes,
Sanja J. Vranes
The Mihailo Pupin Institute, Belgrade, Yugoslavia
Search for more papers by this authorSanja J. Vranes,
Sanja J. Vranes
The Mihailo Pupin Institute, Belgrade, Yugoslavia
Search for more papers by this authorFirst published: 27 December 1999
Abstract
The sections in this article are
- 1 Knowledge Representation
- 2 Logic Programming
- 3 Logic Languages
- 4 Functional Programming Languages
- 5 Hybrid Languages
Bibliography
- 1 A. Barr E. Feigenbaum The Handbook of Artificial Intelligence, London: Pitman, 1983.
- 2 E. Rich Artificial Intelligence, New York: McGraw-Hill, 1983.
- 3 M. Minsky A framework for representing knowledge, in P. Winston (ed.), The Psychology of Computer Vision, New York: McGraw-Hill, 1975.
- 4 A. Newell Production systems: Models of control structures, in W. G. Chase (ed.), Visual Information Processing, New York: Academic Press, 1973.
- 5 B. Kowalski L. Stipp Object processing for knowledge based systems, AI Expert, 5 (10): 34–42, 1990.
- 6 J. Herbrands Research in the theory of demonstration, in J. van Heijenoort (ed.), From Frege to Gödel: A Source Book in Mathematical Logic, Cambride, MA: Harvard University Press, 1967.
- 7
D. Prawitz
An improved proof procedure,
Theoria,
26:
102–139,
1960.
10.1111/j.1755-2567.1960.tb00558.x Google Scholar
- 8
P. C. Gilmore
A proof method for quantification theory,
IBM J. Res. Develop.,
4:
28–35,
1990.
10.1147/rd.41.0028 Google Scholar
- 9 M. Davis H. Putnam A computing for quantification theory, J. Assoc. Comput. Mach., 7: 201–215, 1960.
- 10 J. A. Robinson A machine-oriented logic based on the resolution principle, J. Assoc. Comput. Mach., 12 (1): 23–41, 1965.
- 11 R. A. Kowalski D. Kuehner Linear resolution with selection function, Artif. Intell., 2: 227–260, 1971.
- 12 R. A. Kowalski Logic for Problem Solving, New York: Elsevier North Holland, 1979.
- 13 A. Colmerauer et al. Un Système de Communication Homme–Machine en Français, Groupe de Recherche en Intelligence Artificielle, Universite d'Aix-Marseille, 1973.
- 14 C. Green Applications of theorem proving to problem solving, in Proc. IJCAI '69 Conf., 1969, pp. 219–239.
- 15 P. J. Hayes Computation and deduction, in Proc. MFCS Conf., 1973.
- 16 Amihai Motro Intensional answers to database queries, IEEE Trans. Knowl. Data Eng., 6: 444–454, 1994.
- 17 T. Imieliski Intelligent query answering in rule-based systems, J. Logic Programming, 4 (3): 229–257, 1987.
- 18 L. Cholvy R. Demolombe Querying a rule base, in Proc. 1st Int. Workshop Expert Database Syst., 1984, pp. 326–341.
- 19 A. Pirotte D. Roelants Constraints for improving the generation of intensional answers in deductive database, in Proc. IEEE Comput. Soc. 5th Int. Conf. Data Eng., 1989, pp. 652–659.
- 20 J. Han Chain-split evaluation in deductive databases, IEEE Trans. Knowl. Data Eng., 7: 261–274, 1995.
- 21 S. H. Lee L. J. Henschen Evaluation of recursive queries with extended rules in deductive databases, IEEE Trans. Knowl. Data Eng., 7: 328–332, 1995.
- 22
W. F. Clocksin
C. S. Mellish
Programming in Prolog,
New York:
Springer-Verlag,
1984.
10.1007/978-3-642-96873-0 Google Scholar
- 23 I. Bratko Prolog Programming for Artificial Intelligence, Reading, MA: Addison-Wesley, 1986.
- 24
S. Ceri
G. Gottlog
L. Tanca
What you always wanted to know about Datalog (and never dared to ask),
IEEE Trans. Knowl. Data Eng.,
1:
146–166,
1989.
10.1109/69.43410 Google Scholar
- 25 S. Tsur C. Zaniolo LDL: A logic-based query language, in Proc. 12th Int. Conf. Very Large Data Bases, 1986.
- 26 D. Moon MacLISP Reference Manual, Cambridge, MA: MIT Project MAC, 1974.
- 27 K. M. Pitman The Revised MacLISP Manual, MIT/LCS/TR 295, Cambridge, MA: MIT Laboratory for Computer Science, 1983.
- 28 W. Teitelman InterLISP Reference Manual, Palo Alto, CA: Xerox Palo Alto Research Center, 1978.
- 29 J. McCarthy History of Lisp, in D. Wexelblat (ed.), History of Programming Languages, New York: Academic Press, 1978.
- 30 M. Brinsmead et al. Common Lisp product roundup, AI Expert, 6 (6): 48–57, 1991.
- 31 R. Gabriel LISP: Good news, bad news, how to win big, AI Expert, 6 (6): 31–40, 1991.
- 32 J. Keyes LISP: The great contender, AI Expert, 7 (1): 24–28, 1992.
- 33 Jim Veitch Frames in CLOS, AI Expert, 6 (6): 31–40, 1991.
- 34 M. J. Stefik D. G. Bobrow K. M. Kahn Integrating access-oriented programming into a multiparadigm environment, IEEE Software, 3 (1): 10–18, 1986.
- 35 IntelliCorp Inc., KEE Software Development System User's Manual, Mountain View, CA, 1990.
- 36 Inference Corporation, ART-IM (Automated Reasoning Tool for Information Management) User's Manual, Los Angeles, CA, 1991.
- 37 S. Vranes M. Stanojevic Integrating multiple paradigms within the blackboard framework, IEEE Trans. Softw. Eng., 21: 244–262, 1995.
- 38 A. Frisch A. Cohn 1988 Workshop on Principles of Hybrid Reasoning, AI Mag., 11 (5): 77–84, 1991.
- 39 D. W. Etherington et al. Vivid knowledge and tractable reasoning: Preliminary report, in Proc. 11th Int. Conf. Artificial Intell., 1989, pp. 1146–1152.
- 40 C. Rich The layered architecture of a system for reasoning, in Proc. 6th National Conf. Artificial Intell., 1987, pp. 48–52.
- 41 R. J. Brachman R. E. Fikes H. J. Levesque KRYPTON: A functional approach to knowledge representation, IEEE Computer, 16 (10): 67–73, 1983.
- 42
A. G. Cohn
A more expressive formulation of many sorted logic,
J. Automated Reason.,
3 (2):
113–200,
1987.
10.1007/BF00243207 Google Scholar
- 43 A. M. Frisch A general framework for sorted deduction: Fundamental results on hybrid reasoning, in R. J. Brachman, H. J. Levesque, and R. Reiter (eds.), Proc. 1st Int. Conf. Principles Knowl. Representation Reasoning, Toronto, 1989.
- 44 C. Walther A Many-Sorted Calculus Based on Resolution and Paramodulation, Los Altos, CA: Morgan Kaufman, 1987.
- 45 M. Tokoro Y. Ishikawa Orient/84: A language with multiple paradigms in the object framework, in Proc. Hawaii Int. Conf. Syst. Sci., 1986.
- 46 M. Vilain The restricted language architecture of a hybrid representation system, in Proc. Int. Joint Conf. Artificial Intell., 1985, pp. 547–551.
- 47 M. E. Stickel Automated deduction by theory resolution, in Proc. 9th Int. Joint Conf. Artificial Intell., 1985, pp. 455–458.
- 48 P. Patel-Schneider Decidable first-order logic for knowledge representation, Ph.D. Thesis, University of Toronto, 1987.
- 49 R. McGregor M. H. Burstein Using a description classifier to enhance knowledge representation, IEEE Expert, 6 (3): 41–46, 1991.
- 50 G. Lindstrom P. Panangaden Stream-based execution of logic programs, in Proc. 1984 Int. Symp. Logic Programming, 1984, pp. 168–176.
- 51 G. Lindstrom Functional programming and the logical variable, in Proc. Symp. Principles Programming Languages, 1985, pp. 266–280.
- 52 M. A. Jenkins J. I. Glasgow C. D. McCrosky Programming styles in Nial, IEEE Software, 3 (1): 46–55, 1986.
- 53 K. Weiskamp T. Hengl Artificial Intelligence Programming with Turbo Prolog, New York: Wiley, 1988.
- 54 T. Shintani et al. KORE: A Hybrid Knowledge Programming Environment for Decision Support Based on a Logic Programming Language, in Proc. 5th Conf. Symp. Logic Programming, 1986.
- 55 P. Devanbu M. Freeland S. Naqvi A procedural approach to search control in Prolog, in Proc. Int. Conf. ECAI'86, 1986.
- 56 M. Dincbas J.-P. La Pape Metacontrol of Logic Programs in METALOG, in Proc. Int. Conf. 5th Generation Comput. Syst. 1984, 1984.
- 57
H. Gallaire
J. Minker
J. Nicolas (eds.)
Advances in Database Theory,
Vol. 1, New York:
Plenum Press,
1981.
10.1007/978-1-4615-8297-7 Google Scholar
- 58 S. Vranes M. Stanojevic Prolog/Rex—a way to extend Prolog for better knowledge representation, IEEE Trans. Knowl. Data Eng., 6: 22–37, 1994.
- 59 T. Shintani A fast Prolog based production system KORE/IE, in Proc. 5th Conf. Symp. Logic Programming, 1986.
- 60 L. Console G. Rossi Using Prolog for building FROG, a hybrid knowledge representation system, New Generation Comput., 6: 361–388, 1989.
- 61 J. S. Aikins A representation scheme using both frames and rules, in B. G. Buchanan and E. Shortlife (eds.), Rule Based Expert Systems, Reading, MA: Addison-Wesley, 1984.
- 62
D. G. Bobrow
T. Winograd
An overview of KRL-0, a knowledge representation language,
Cognitive Sci.,
1,
1977.
10.1207/s15516709cog0101_2 Google Scholar
- 63 R. B. Roberts I. P. Goldstein The FRL manual, MIT AI-Memo 409, Cambridge, MA: MIT, 1977.
- 64 R. J. Brachman J. G. Schmolze An overview of the KL-ONE knowledge representation system, Cognitive Sci., 9: 171–216.
- 65 C. Hewitt Description and theoretical analysis (using schemas) of PLANNER: A language for proving theorems and manipulating models in a robot, Doctoral Dissertation, AI Laboratory, Massachusetts Institute of Technology, 1971.
- 66 G. J. Sussman D. McDermott Why conniving is better than planning, Technical Report, AI Memo 2655A, Cambridge, MA: Massachusetts Institute of Technology, 1972.
Wiley Encyclopedia of Electrical and Electronics Engineering
Browse other articles of this reference work: