Some notes on knowledge assimilation in deductive databases

  • Hendrik Decker
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1472)


This paper is intended to serve as a background for studies in the field of knowledge assimilation in deductive databases. Rather than presenting a formal theory or a technical methodology, it provides a largely informal overview of some of the constituent issues of knowledge assimilation. Various tasks of knowledge assimilation, particularly those related to the integrity-preserving satisfaction of update requests, are discussed. Also the use of abductive logic programming for knowledge assimilation is addressed. Close interrelationships of seemingly disconnected tasks such as query answering, updating, default reasoning, belief revision, and of the underlying inference principles of deduction and abduction, are pointed out. Particular attention is paid to the various kinds of hypotheses used in abductive logic programming for implementing knowledge assimilation.


Logic Program Logic Programming Belief Revision Integrity Constraint Horn Clause 
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. [ABe]
    Apt, Bezem: Acyclic programs. Proc. 7th ICLP. MIT Press, 1990.Google Scholar
  2. [ABo]
    Apt, Bol: Logic programming and negation: a survey. J. Logic Programming 19/20, 1994.Google Scholar
  3. [AD]
    Aravindan, Dung: Knowledge base dynamics, abduction, and database updates. J. Applied Non-Classical Logics 5, 1994.Google Scholar
  4. [AGM]
    Alchourrón, Gärdenfors, Makinson: On the logic of theory change: Partial meet contraction and revision functions. Journal of Symbolic Logic 50, 1985.Google Scholar
  5. [Ar]
    Armstrong: Dependency structures of data base relationships. Proc. IFIP '74. North-Holland, 1974.Google Scholar
  6. [AV]
    Abiteboul, Vianu: Transactions and integrity constraints. Proc. PoDS'85. ACM Press, 1985.Google Scholar
  7. [BAN]
    Burrows, Abadi, Needham: A logic of authentication. DEC Systems Research Centre Report 39, 1989.Google Scholar
  8. [BB]
    Bernstein, Blaustein: Fast methods for testing quantified relational calculus assertions. Proc. Int'l Conf. Management of Data. ACM Press, 1982.Google Scholar
  9. [BBC]
    Bernstein, Blaustein, Clarke: Fast maintenance of semantic integrity assertions using redundant aggregate data. Proc. 6th VLDB, 1980.Google Scholar
  10. [Bc]
    Bocca: MegaLog — A platform for developing knowledge base management systems. Proc. Int'l Symposium on Database Systems for Advanced Applications. DASFAA Press, 1991.Google Scholar
  11. [Bc+]
    Bocca, Decker, Nicolas, Vieille, Wallace: Some steps towards a DBMS-based KBMS. In Kugler (ed): Information Processing (Proc. IFIP'86), 1986.Google Scholar
  12. [BDM]
    Bry, Decker, Manthey: A uniform approach to constraint satisfaction and constraint satisfiability in deductive databases. Proc. 1st EDBT. Springer, 1988.Google Scholar
  13. [BK]
    Bowen, Kowalski: Amalgamating language and metalanguage in logic programming. In Clark, Tärnlund (eds): Logic Programming. Academic Press, 1982.Google Scholar
  14. [BL]
    Brachman, Levesque (eds): Readings in Knowledge Representation. Morgan Kaufmann, 1985.Google Scholar
  15. [Bn+]
    Bonandrenko, Dung, Kowalski, Toni: An abstract, argumentation-theoretic approach to default reasoning., 1997.Google Scholar
  16. [BTK]
    Bonandrenko, Toni, Kowalski: An assumption-based framework for nonmonotonic reasoning. Proc. 2nd Int'l Workshop Logic Programming and Nonmonotonic Reasoning. MIT Press, 1993.Google Scholar
  17. [CA]
    Christiansen, Andreasen: A practical approach to hypothetical database queries. In this volume, 1998.Google Scholar
  18. [CaD]
    Casamayor, Decker: Hypothetical query answering in first-order databases. DSIC, Universidad Politécnica de Valencia; short version in Proc. SCAI'95. IOS Press/Ohmsha, 1995.Google Scholar
  19. [Ca+]
    Cast, Fugini, Martella, Samarati: Database Security. ACM Press, 1994.Google Scholar
  20. [CCD]
    Celma, Casamayor, Decker: Improving integrity checking by compiling derivation paths. In [OP], 1993.Google Scholar
  21. [CeD]
    Celma, Decker: Integrity checking in deductive databases — the ultimate method? Proc. 5th Australasian Database Conference. Global Publication Services, 1994.Google Scholar
  22. [CGM]
    Chakravarthy, Grant, Minker: Logic-based approach to semantic query optimization. ACM Transactions on Database Systems 15, 1990.Google Scholar
  23. [Cl]
    Clark: Negation as failure. In [GM1], 1978.Google Scholar
  24. [CM]
    Charniak, McDermott: Introduction to Artificial Intelligence. AddisonWesley, 1985.Google Scholar
  25. [Co1]
    Codd: A relational model of data for large shared data banks. Communications of the ACM 13, 1970.Google Scholar
  26. [Co2]
    Codd: Relational completeness of data base sublanguages. In Rustin (ed): Data Base Systems. Prentice-Hall, 1972.Google Scholar
  27. [CP]
    Cox, Pietrzykowski: Causes for events: Their computation and applications. Proc. 8th CADE. Springer, 1986.Google Scholar
  28. [CS]
    Coffey, Saidha: Logic for verifying public-key cryptographic protocols. IEE Proc. Computers and Digital Techniques 144, 1997.Google Scholar
  29. [D1]
    Decker: Integrity enforcement on deductive databases. In Kerschberg (ed): Expert Database Systems. Morgan Kaufmann, 1987.Google Scholar
  30. [D2]
    Decker: The range form of databases and queries, or: How to avoid floundering. Proc. 5. öGAI, Springer, 1989.Google Scholar
  31. [D3]
    Decker: Drawing updates from derivations. ECRC Technical Report KB-65, 1989. Short version in Proc. 3rd ICDT; Springer, 1990.Google Scholar
  32. [D4]
    Decker: On generalized cover axioms. Proc. 8th ICLP. MIT Press, 1991.Google Scholar
  33. [D5]
    Decker: On explanations in deductive databases. Proc. 3rd Workshop on Foundations of Models and Languages for Data and Objects. Informatik-Bericht 91/3, TU Clausthal, 1991.Google Scholar
  34. [D6]
    Decker: An extension of SLD by abduction and integrity maintenance for view updating in deductive databases. Proc. JICSLP'96. MIT Press, 1996.Google Scholar
  35. [D7]
    Decker: A model-theoretic semantics of integrity constraints in deductive databases. Proc. ILPS'97 Workshop Logic Programming & Knowledge Representation (LPKR'97), 1997.Google Scholar
  36. [D8]
    Decker: One abductive logic programming procedure for two kinds of updates. Proc. DYNAMICS'97 (ILPS'97 Workshop), 1997.Google Scholar
  37. [D9]
    Decker: Abduction for knowledge assimilation in deductive databases. Proc. 17th Int'l Conf. of the Chilean Computer Society (SCCC'97). IEEE Press, 1997.Google Scholar
  38. [D10]
    Decker: Toward a paraconsistent semantics of database integrity., 1997. Abstract: Scholar
  39. [D11]
    Decker: Aspects of paraconsistency in deductive databases., 1997.Google Scholar
  40. [D12]
    Decker: On knowledge assimilation in deductive databases., 1998.Google Scholar
  41. [DC]
    Decker, Celma: A slick procedure for integrity checking in deductive databases, Proc. 11th ICLP. MIT Press, 1994.Google Scholar
  42. [Di1]
    Dix: Classifying semantics of logic programs. In Nerode, Marek, Subrahmanian (eds): Logic Programming and Non-Monotonic Reasoning (Proc. 1st Int'l Workshop LPNMR). MIT Press, 1991.Google Scholar
  43. [Di2]
    Dix: A framework for representing and characterizing semantics of logic programs. In Nebel, Rich, Swartout (eds): Principles of Knowledge Representation and Reasoning (Proc. 3rd Int'l Conf., KR'92). Morgan Kaufmann, 1992.Google Scholar
  44. [DKT]
    Dung, Kowalski, Toni: Argumentation-theoretic proof procedures for default reasoning., 1997.Google Scholar
  45. [Dl]
    Dahl: Logic programming as a representation of knowledge. The Computer Journal 26, 1983.Google Scholar
  46. [Ds]
    Das: Deductive Databases and Logic Programming. Addison-Wesley, 1992.Google Scholar
  47. [DTU]
    Decker, Teniente, Urpí: How to tackle schema validation by view updating. Proc. 5th EDBT. Springer, 1996.Google Scholar
  48. [Du]
    Dung: An argumentation-theoretic foundation for logic programming. J. Logic Programming 22, 1995.Google Scholar
  49. [DW]
    Das, Williams: A path finding method for constraint checking in deductive databases. Data & Knowledge Engineering 4, 1989.Google Scholar
  50. [EC]
    Eswaran, Chamberlin: Functional specifications of a subsystem for data base integrity. Proc. 1st VLDB, 1975.Google Scholar
  51. [EK]
    Eshghi, Kowalski: Abduction compared with negation by failure. Proc. 7th ICLP. MIT Press, 1989.Google Scholar
  52. [EvK]
    Evans, Kakas: Hypothetico-deductive reasoning. Proc. 5th FGCS, Vol. 2. Ohmsha/IOS Press, 1992.Google Scholar
  53. [FK]
    Fung, Kowalski: The iff procedure for abductive logic programming. J. Logic Programming 33, 1997.Google Scholar
  54. [Fla]
    Flach: Towards inductive logic databases — From extensional to intensional knowledge. In this volume, 1998.Google Scholar
  55. [Flo]
    Florentin: Consistency auditing of databases. The Computer Journal 17, 1974.Google Scholar
  56. [Fra]
    Fraser: Integrity of a mass storage filing system. The Computer Journal 12, 1969.Google Scholar
  57. [Fre]
    Freeston: Begriffsverzeichnis: a concept index, in Worboys, Grundy (eds): Advances in Databases (Proc. 11th British National Conf. on Databases). Springer, 1989.Google Scholar
  58. [FSH]
    Farley, Stearns, Hsu: LAN Times Guide to Security and Data Integrity. McGraw-Hill, 1996.Google Scholar
  59. [FSW]
    Fernandez, Summers, Wood: Database Security and Integrity. AddisonWesley, 1980.Google Scholar
  60. [FU]
    Fayyad, Uthurusamy (eds): Data mining and knowledge discovery in databases. Communications of the ACM 39, 1996.Google Scholar
  61. [FW]
    Frost, Whittaker: A step towards the automatic maintenance of the semantic integrity of databases. The Computer Journal 26, 1983.Google Scholar
  62. [Gä1]
    Gärdenfors: Knowledge in Flux. MIT Press, 1988.Google Scholar
  63. [Gä2]
    Gärdenfors (ed): Belief Revision. Cambridge University Press, 1992.Google Scholar
  64. [GFP]
    Goebel, Furukawa, Poole: Using definite clauses and integrity constraints as the basis for a theory formation approach. Proc. 3rd ICLP. Springer, 1986.Google Scholar
  65. [Gi]
    Ginsberg: Knowledge-base reduction: A new approach to checking knowledge bases for inconsistency & redundancy. Proc. AAAI'88, 1988.Google Scholar
  66. [GLi]
    Gelfond, Lifschitz: The stable model semantics for logic programming. Proc. 5th ICLP. MIT Press, 1988.Google Scholar
  67. [GLI]
    Guessoum, Lloyd: Updating knowledge bases I/II. New Generation Computing 8/10, 1990/1991.Google Scholar
  68. [GLü]
    Griefahn, Lüttringhaus: Top-down integrity constraints checking for deductive databases. Proc. ICLP'90. MIT Press, 1990.Google Scholar
  69. [GM1]
    Gallaire, Minker (eds): Logic and Data Bases. Plenum Press, 1978.Google Scholar
  70. [GM2]
    Gal, Minker: Informative and cooperative answers in databases using integrity constraints. In Dahl, Saint-Dizier (eds): Natural Language Understanding and Logic Programming. North-Holland, 1988.Google Scholar
  71. [GMN]
    Gallaire, Minker, Nicolas: Logic and databases: A deductive approach. Computing Surveys 16, 1984.Google Scholar
  72. [GR]
    Green, Raphael: The use of theorem-proving techniques in question-answering systems. Proc. 23rd Nat'l Conf. of the ACM. Brandon Systems Press, Thompson Book Company, 1968.Google Scholar
  73. [Gr+]
    Gray, Bosworth, Layman, Pirahesh: Data cube: a relational aggregation operator generalizing group-by, cross-tab, and sub-totals. Microsoft Technical Report, 1995.Google Scholar
  74. [Gu+]
    Gupta, Sagiv, Ullman, Widom: Constraint checking with partial information. Proc. PoDS'94. ACM Press, 1994.Google Scholar
  75. [HaM]
    Hammer, McLeod: Semantic integrity in relational data base systems. Proc. 1st VLDB, 1975.Google Scholar
  76. [HeM]
    Henschen, McCune: Maintaining state constraints in relational databases: A proof theoretic basis. J. ACM 36, 1989.Google Scholar
  77. [HI]
    Hsu, Imielinski: Integrity checking for multiple updates, SIGMoD'85. ACM Press, 1985.Google Scholar
  78. [HMN]
    Henschen, McCune, Naqvi: Compiling constraint-checking programs from firstorder formulas. In Gallaire, Minker, Nicolas (eds): Advances in Data Base Theory, Vol. 2. Plenum Press, 1984.Google Scholar
  79. [HS]
    Hammer, Sarin: Efficient monitoring of database assertions. Proc. SIGMoD '78. ACM Press, 1978.Google Scholar
  80. [HW]
    Hartshorne, Weiss (eds): Collected Papers of Charles Sanders Peirce, Harvard University Press, 1933.Google Scholar
  81. [Kb]
    Kobayashi: Validating database updates. Information Systems 9, 1984.Google Scholar
  82. [Ki+]
    Kitakami, Kunifuji, Miyachi, Furukawa: A methodology for implementation of knowledge acquisition systems. Proc. Int'l Symposium on Logic Programming. IEEE Press, 1984.Google Scholar
  83. [KKR]
    Kanellakis, Kuper, Revesz: Constraint query languages. Proc. PoDS'90. ACM Press, 1990.Google Scholar
  84. [KKT]
    Kakas, Kowalski, Toni: The role of abduction in logic programming. In Gabbay, Hogger, Robinson (eds): Handbook of Logic in Artificial Intelligence and Logic Programming, Vol. 5. Oxford University Press, 1998.Google Scholar
  85. [KLM]
    Kraus, Lehmann, Magidor: Nonmonotonic reasoning, preferential models and cumulative logics, Artificial Intelligence 44, 1990.Google Scholar
  86. [KM1]
    Kakas, Mancarella: Database updates through abduction. Proc. 16th VLDB, 1990Google Scholar
  87. [KM2]
    Kakas, Mancarella: Knowledge assimilation and abduction. In Martins, Reinfrank (eds): Truth Maintenance Systems (Proc. ECAI'90 Workshop). Springer, 1991.Google Scholar
  88. [Kn]
    Konolige: A general theory of abduction, Proc. AAAI Spring Symposium on Automated Abduction. Stanford University Press, 1990.Google Scholar
  89. [Ko1]
    Kowalski: Predicate logic as a programming language. Proc. IFIP'74. NorthHolland, 1974.Google Scholar
  90. [Ko2]
    Kowalski: Logic for data description. In [GM], 1978.Google Scholar
  91. [Ko3]
    Kowalski: Logic for Problem Solving. North-Holland, 1979.Google Scholar
  92. [Ko4]
    Kowalski: The limitations of logic and its role in artificial intelligence. In Schmidt, Thanos (eds): Foundations of Knowledge Base Management: Contributions from Logic, Databases and AI. Springer, 1989.Google Scholar
  93. [Ko5]
    Kowalski: Problems and promises of computational logic. In Lloyd (ed): Computational Logic. Springer, 1990.Google Scholar
  94. [Ko6]
    Kowalski: Using meta-logic to reconcile reactive with rational agents. In Apt, Turini (eds): Meta-Logic and Logic Programming. MIT Press, 1995.Google Scholar
  95. [KS1]
    Kowalski, Sadri: Knowledge representation without integrity constraints. Imperial College, 1988.Google Scholar
  96. [KS2]
    Kowalski, Sadri: Logic programs with exceptions. Proc. 7th ICLP. MIT Press, 1990.Google Scholar
  97. [KS3]
    Kowalski, Sadri: Towards a unified agent architecture that combines rationality with reactivity. In Pedreschi, Zaniolo (eds): Logic in Databases (Proc. Int'l Workshop). Springer, 1996.Google Scholar
  98. [KTW]
    Kowalski, Toni, Wetzel: Executing suspended logic programs. Fundamenta Informaticae, to appear, 1998.Google Scholar
  99. [Kü]
    Küchenhoff: On the efficient computation of the difference between consecutive database states. Proc. DOOD'91. Springer, 1991.Google Scholar
  100. [Li]
    Liben (ed): Piaget and The Foundations of Knowledge. Erlbaum, 1983.Google Scholar
  101. [LL]
    Lee, Ling: Further improvement of integrity constraint checking for stratifiable deductive databases. Proc. 22nd VLDB, 1996.Google Scholar
  102. [Ll]
    Lloyd: Foundations of Logic Programming. Springer, 1987.Google Scholar
  103. [LM]
    Leuschel, Martens: Partial deduction of the ground representation and its application to integrity checking. Proc. ILPS'95. MIT Press, 1995.Google Scholar
  104. [LST]
    Lloyd, Sonenberg, Topor: Integrity constraint checking in stratified databases. J. Logic Programming 4, 1987.Google Scholar
  105. [LT]
    Lloyd, Topor: Making Prolog more expressive. J. Logic Programming 3, 1984.Google Scholar
  106. [LTW]
    Lawley, Topor, Wallace: Using weakest preconditions to simplify integrity constraints checking. In [OP], 1993.Google Scholar
  107. [MC1]
    McCarthy: First order theories of individual concepts and propositions. In D. Michie (ed): Machine Intelligence 9. University of Edinburgh Press, 1979.Google Scholar
  108. [MC2]
    McCarthy: Applications of circumscription to formalizing commonsense knowledge. Artificial Intelligence 28, 1986.Google Scholar
  109. [Mi+]
    Miyachi, Kunifuji, Kitakami, Furukawa, Takeuchi, Yokota: A knowledge assimilation method for logic databases. New Generation Computing 2, 1984.Google Scholar
  110. [Mr1]
    Minker (ed): Foundations of Deductive Databases and Logic Programming. Morgan Kaufmann, 1988.Google Scholar
  111. [Mr2]
    Minker: Perspectives in deductive databases. J. Logic Programming 5, 1988.Google Scholar
  112. [Mr3]
    Minker: Logic and databases — past, present and future. AI Magazine 18, 1997.Google Scholar
  113. [Mu]
    Muggleton: Inductive Acquisition of Expert Knowledge. Addison-Wesley, 1989.Google Scholar
  114. [My1]
    Minsky: On interaction with data bases. Proc. SIGFIDET Workshop on Data Description, Access and Control. ACM Press, 1974.Google Scholar
  115. [My2]
    Minsky: Logical vs. analogical or symbolic vs. connectionist or neat vs. scruffy. In P. H. Winston, S.A. Shellard (eds): Artificial Intelligence at MIT, Vol. 1. MIT Press, 1990.Google Scholar
  116. [Ni]
    Nicolas: Logic for improving integrity checking in relational data bases. Acta Informatica 18, 1982.Google Scholar
  117. [NY1]
    Nicolas, Yazdanian: Integrity checking in deductive data bases. In [GM], 1978.Google Scholar
  118. [NY2]
    Nicolas, Yazdanian: An outline of BDGEN: A deductive DBMS. In Mason (ed): Information Processing (Proc. IFIP'83), 1983.Google Scholar
  119. [Ol]
    Olivé: Integrity constraints checking in deductive databases. Proc. 17th VLDB, 1991.Google Scholar
  120. [OP]
    Orlowska, Papazoglu (eds): Advances in Database Research (Proc. 4th Australian Database Conf.). World Scientific, 1993.Google Scholar
  121. [PGA]
    Poole, Goebel, Aleliunas: Theorist: A logical reasoning system for defaults and diagnosis. In Cercone, McCalla (eds): The Knowledge Frontier: Essays in the Representation of Knowledge. Springer, 1987.Google Scholar
  122. [Pl]
    Pople: On the mechanization of abductive logic. Proc. IJCAI'73. Morgan Kaufmann, 1973.Google Scholar
  123. [Po1]
    Poole: A logical framework for default reasoning. Artificial Intelligence 36, 1988.Google Scholar
  124. [Po2]
    Poole: Explanation and prediction: An architecture for default and abductive reasoning. Computational Intelligence 5, 1989.Google Scholar
  125. [Pp]
    Popper: The Logic of Scientific Discovery. Hutchinson, 1959.Google Scholar
  126. [Pr]
    Przymusinski: On the declarative semantics of deductive databases and logic programs. In [Mr1], 1988.Google Scholar
  127. [Q+]
    Quass, Rajaraman, Sagiv, Ullman, Widom: Querying seminstructured heterogeneous information. Anonymous ftp pub/quass/1994/ at, 1994.Google Scholar
  128. [R1]
    Reiter: A logic of default reasoning. Artificial Intelligence 13, 1980.Google Scholar
  129. [R2]
    Reiter: On the integrity of typed first order data bases. In Gallaire, Minker, Nicolas (eds): Advances in Data Base Theory, Vol. 1. Plenum Press, 1981.Google Scholar
  130. [R3]
    Reiter: Towards a logical reconstruction of relational database theory. In Brodie, Mylopoulos, Schmidt (eds): On Conceptual Modelling. Springer, 1984.Google Scholar
  131. [RdK]
    Reiter, de Kleer: Foundations of assumption-based truth maintenance systems. Proc. AAAI'87, 1987.Google Scholar
  132. [RU]
    Ramakrishnan, Ullman: A survey of deductive database systems. J. Logic Programming 23, 1995.Google Scholar
  133. [SZ]
    Saccá, Zaniolo: Stable models and non-determinism in logic programs with negation. Proc. PoDS'90. ACM Press, 1990.Google Scholar
  134. [Sa]
    Sandhu: On five definitions of data integrity. In Keefe, Landwehr (eds): Database Security VII. Elsevier, 1994.Google Scholar
  135. [Se]
    Sergot: A query-the-user facility for logic programming. In Degano, Sandevall (eds): Integrated Interactive Computer Systems. North-Holland, 1983.Google Scholar
  136. [Si]
    Simmons (ed): Contemporary Cryptology: The Science of Information Integrity. IEEE Press, 1992.Google Scholar
  137. [SK]
    Sadri, Kowalski: A theorem-proving approach to database integrity. In [Mr1], 1988.Google Scholar
  138. [St]
    Stonebraker: Implementation of integrity constraints and views by query modification. Proc.SIGMoD'75. ACM Press, 1975.Google Scholar
  139. [Te]
    Tennent: On having bad contractions, or: No room for recovery. J. Applied Non-Classical Logics 7, 1997.Google Scholar
  140. [TK]
    Toni, Kowalski: Reduction of abductive logic programs to normal logic programs. Proc. 12th ICLP. MIT Press, 1995.Google Scholar
  141. [TO]
    Teniente, Olivé: Updating knowledge bases while maintaining their consistency. VLDB Journal 4, 1995.Google Scholar
  142. [To]
    Tomasic: View update translation via deduction and annotation. Proc. 2nd ICDT. Springer, 1988.Google Scholar
  143. [Ul]
    Ullman: Principles of Database and Knowledge-Base Systems, Vol. 1/2. Computer Science Press, 1988/1989.Google Scholar
  144. [Wa]
    Wallace: Compiling integrity checking into update procedures. Proc. 12th IJCAI, 1991.Google Scholar
  145. [WC]
    Widom, Ceri (eds): Active Database Systems. Morgan Kaufmann, 1996.Google Scholar
  146. [Wd]
    Widom (ed): IEEE Data Engineering Bulletin 18, special issue on Materialized Views and Data Warehousing, 1995.Google Scholar
  147. [Wk]
    Wilkes: On preserving the integrity of data bases. The Computer Journal 15, 1972.Google Scholar
  148. [Wm]
    Williams: Applications of belief revision. In this volume, 1998.Google Scholar
  149. [WSK]
    Weber, Stucky, Karszt: Integrity checking in data base systems. Information Systems 8, 1983.Google Scholar
  150. [YS]
    YalÇinalp, Sterling: An integrated interpreter for explaining Prolog's successes and failures. In Abramson (ed): Meta-Programming in Logic Programming. MIT Press, 1989.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Hendrik Decker
    • 1
  1. 1.Institut für InformatikLudwig-Maximilians-Universität MünchenGermany

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