Kore : A hybrid knowledge programming environment for decision support based on a logic programming language

  • Toramatsu Shintani
  • Yoshinori Katayama
  • Kunihiko Hiraishi
  • Mitsuhiko Toda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 264)


We discuss problems to construct intelligent decision support systems, and propose KORE (Knowledge Oriented Reasoning Environment) as an environment for developing such systems. KORE is a hybrid tool for assisting unified knowledge-based program construction, and is composed of four subsystems. Each of the subsystems provides a unique knowledge programming paradigm which is object-oriented (e.g., SMALLTALK), data-oriented (e.g., demons), rule-oriented (e.g., OPS5), network-oriented (e.g., semantic networks), or logic-oriented (e.g., Prolog) programming paradigm. These subsystems can be integrated by using a relational table based on a logic programming language, which is used as a common internal representation for information. The integration by the relational table enables to provide a unifying principle for the different programming paradigms. KORE can offer a hybrid environment to solve problems on intelligent decision support systems.


Logic Programming Belief Revision Inference Engine Relational Table Logic Programming Language 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Alter SL (1980) Decision Support System: Current Practice and Continuing Challenges. Addison-Wesley, Mass., p316Google Scholar
  2. Astrahan MM (1975) Implementation of a Structured English Query Language. Communications of ACM, 18:580–589Google Scholar
  3. Bobrow DG, Stefik MJ (1983) The LOOPS Manual. KB-VLISI-81-13Google Scholar
  4. Bobrow DG (1984) IF PROLOG IS ANSWER WHAT IS THE QUESTION. Proc. The International Conference on Fifth Generation Computer System, 138–145Google Scholar
  5. Brachman RJ (1983) What IS-A is and isn't: An Analysis of Taxonomic Links in Semantic Networks. Computer 16 (October): 30–36Google Scholar
  6. Dahl V (1978) On Database Systems Development Through Logic. ACM Transactions on Database Systems 7:102–123Google Scholar
  7. Doyle J (1978) Truth Maintenance System for Problem Solving. MIT, AI-TR-419Google Scholar
  8. Fikes R, Kehler T (1985) The Role of Frame-Based Representation in Reasoning. Communication of the ACM 28: 904–920Google Scholar
  9. Forgy CL (1981) OPS5 User's Manual. CMU-CS-81-135, JulyGoogle Scholar
  10. Forgy CL (1982) Rete: A Fast Algorithm for the Many Pattern/ Many Object Pattern Match Problem. Artificial Intelligence 19: 17–37Google Scholar
  11. Goldberg I, Robson D (1983) Smalltalk-80: The Language and it's Implementation. Addison-Wesley, Mass., p714Google Scholar
  12. Gorry GA, Morton MSS (1971) A Framework for Management Information Systems. Sloan Management Review 13: 55–70Google Scholar
  13. Hayes-Roth F (1984) The Knowledge-Based Expert System: A tutorial. Computer 17 (September): 11–28Google Scholar
  14. Keen PGW, Morton MSS (1978) Decision Support Systems: An Organizational Perspective. Addison Wesley, Mass, p264Google Scholar
  15. Keeney RL, Raiffa H (1976) Decisions with Multiple Objectives: Preferences and Value Tradeoffs. Wiley, p569Google Scholar
  16. Kowalski R (1977) Logic for Problem Solving. Elservier North Holland, 31–44Google Scholar
  17. Kowalski R (1978) LOGIC FOR DATA DESCRIPTION. In: Gallaire H (ed) LOGIC AND DATA BASES, Plenum Press, New YorkGoogle Scholar
  18. McDermott D (1983) Contexts and Data Dependencies: A Synthesis. IEEE, PAMI-5: 237–246Google Scholar
  19. Sacerdoti ED (1974) Planning in a hierarchy of abstraction spaces. Artificial Intelligence 13: 81–132Google Scholar
  20. Schneider HJ, Whinston A (1985) Editorial. Decision Support Systems 1: 1–4Google Scholar
  21. Simon HA (1960) The New Science of Management Decision. New York: Harper & RowGoogle Scholar
  22. Shintani T (1986) Knowledge Table: An Approach to Knowledge Utilization Mechanism for Knowledge Base. FUJITSU IIAS-SIS Research Report No. 70, p32Google Scholar
  23. Stallman RM, Sussman GJ (1977) Forward Reasoning and Dependency-Directed Backtracking in a System for Computer-Aided Circuit Analysis. Artificial Intelligence 9: 135–196Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1987

Authors and Affiliations

  • Toramatsu Shintani
    • 1
  • Yoshinori Katayama
    • 1
  • Kunihiko Hiraishi
    • 1
  • Mitsuhiko Toda
    • 1
  1. 1.International Institute for Advanced Study of Social Information Science (IIAS-SIS)Fujitsu LimitedNumazu-shi, ShizuokaJapan

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