Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-26T20:31:42.494Z Has data issue: false hasContentIssue false
  • English
  • Français

State-of-the-art report on reactive processing in databases and artificial intelligence

Published online by Cambridge University Press:  07 July 2009

Petra Bayer
Petra Bayer
Affiliation:
ECRC, Arabellastr. 17, D-8000 Munich 81, Germany
Get access Rights & Permissions [Opens in a new window]

Abstract

Active rules have been a standard technique in artificial intelligence (AI) for almost two decades. Variants of the Al methods are currently being adapted to provide database systems with the ability to respond reactively to events and database state changes. This paper gives an overview of developments in reactive processing database research, concentrating on active databases that are integrated with relational and object-oriented systems. A general presentation of “trigger”-based processing techniques is given, with a detailed review of active relational and object-oriented database models. An overview of technologies for active processing in AI is also presented, and some common and contrasting themes in database and AI technology identified.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 8 , Issue 2 , June 1993 , pp. 145 - 171
Copyright
Copyright © Cambridge University Press 1993

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agrawal, R, Cochrane, R and Lindsay, B, 1991, “On Maintaining Priorities in a Production Rule System” In: Camps, Lohman S, ed., Proceedings 17th VLDB Conference pp 479–487, Barcelona.Google Scholar
Aiken, A, Widom, J and Hellerstein, JM, 1992, “Behaviour of Database Production Rules: Termination, Confluence, and Observable Determinism” In: Proceedings ACM SIGMOD tnt. Conf on Management of Data, San Diego, CA.Google Scholar
Anderson, JA, 1983, The Architecture of Cognition Harvard University Press.Google Scholar
Bahr, E, Barachini, F and Mistelberger, H, 1992, “A New Parallelization Method for Production Systems” In: Proceedings hit. Conf. on Fifth Generation Computer Systems pp 969–976, Tokyo, Japan.Google Scholar
Bancilhon, F, Delobel, C and Kanellakis, P, 1992, Building an Object-Oriented Database System: the story of 02 Morgan Kaufmann.Google Scholar
Barthcz, M, Kiernan, G, Maindreville, C and Simon, E, 1988, “An Overview of the RDLI Deductive Database System” Technical Report N-1133, INRIA, Rocquencourt, France.Google Scholar
Been, C and Milo, T, 1991, “A Model for Active Object Oriented Database” In: Camps Lohman S, ed., Proceedings 17th VLDB Conference pp 337–349, Barcelona.Google Scholar
Blakeley, JA, Coburn, N and Larson, P, 1989, “Updating Derived Relations: Detecting Irrelevant and Autonomously Computable Updates”. ACM Trans. Database Systems. 14(3) 369–400, 09.CrossRefGoogle Scholar
Buchanan, BG and Mitchell, T, 1978, “Model-directed learning by production rules” In: Waterman, DA and Hayes-Roth, F, eds., Pattern-Directed Inference Systems Academic Press.Google Scholar
Buneman, OP and Clemons, EK, 1979, “Efficiently Monitoring Relational Databases” ACM Trans. Database Systems. 4(3) 368–382, 09.CrossRefGoogle Scholar
Cacace, F and Ceri, S, 1990, “Integreating Object-Oriented Data Modelling with a Rule-Based Programming Paradigm” In: Garcia-Molina H and Jagadish HV, eds., Proceedings ACM Conference on the Management of Data (SIGMOD) pp 225–236, Atlantic City, 05.CrossRefGoogle Scholar
Caseau, Y, 1991, “An Object-Oriented Deductive Language”, Ann. Mathematics and Artificial Intelligence 3.Google Scholar
Ceri, S, Gottlob, G and Tanca, L, 1989, “What You Always Wanted to Know About Datalog (And Never Dared to Ask)” IEEE Trans. Knowledge and Data Engineering 1(1) 146–166, 03.Google Scholar
Ceri, S, Gottlob, G and Tanca, L, 1990, Logic Programming and Databases Springer-Verlag.CrossRefGoogle Scholar
Ceri, S and Widom, J, 1990, “Deriving Production Rules for Constraint Maintenance” In: McLcod, ed., Proceedings 16th VLDB Conference pp 566–577, Brisbane, 08.Google Scholar
Ceri, S and Widom, J, 1992-a, “Deriving Incremental Production Rules for Deductive Data” Rapporto interno n. 92-081, Politecnico di Milano.Google Scholar
Ceri, S and Widom, J, 1992-b, “Production Rules in Parallel and Distributed Database Environments” In: Yuan, , ed., Proceedings 18th VLDB Conference pp 339–351, Vancouver, Canada, August.Google Scholar
Chakravarthy, S, 1989, “Rule Management and Evaluation: An Active DBMS Perspective” S1GMOD REC., Special issue on Rule Management and Processing in Expert Database Systems 18(3),09.Google Scholar
Chomsky, AN 1957, Syntactic Structures The Hague: Mouton.Google Scholar
Cooper, R, Fox, J, Farringdon, J and Shallice, T, 1992, “Towards a systematic methodology for cognitive modelling”.Google Scholar
Czejdo, B, Eick, Ch and Taylor, M, 1991, “TANGUY: Integrating Database, Rule-based and Object- Oriented Paradigms” In: 2nd International Symposium on Database Systems for Advanced Applications pp 339–346, Tokyo, 04.Google Scholar
Davis, R, 1980, “Meta-rules: reasoning about control” Artificial Intelligence 15(3).Google Scholar
Davis, R, 1982, “Applications of meta-level knowledge to the construction, maintenance and use of large knowledge bases” In: Davis, R and Lenat, DB, eds., Knowledge-based Systems in Artificial Intelligence McGraw-Hill.Google Scholar
Davis, R and King, J, 1976, “An overview of production systems” In: Elcock, EW and Michie, D, eds., 1976, Machine Intelligence vol 8 Wiley, 300–332.Google Scholar
Diaz, O, Paton, N and Gray, P, 1991, “Rule Management in Object Oriented Databases: A Uniform Approach” In: Camps Lohman, S, ed., Proceedings 17th VLDB Conference pp 317–326, Barcelona, 09.Google Scholar
Erman, LD, Hayes-Roth, VR, Lesser, VR and Reddy, RD, 1980, “The HEARSAY-Il speech understanding system: Integrating knowledge to resolve uncertainty” ACM Computing Surveys 12(2).Google Scholar
Forgy, CL, 1982, “Rete: a fast algorithm for the man pattern/many object pattern match problem” Artificial Intelligence 19(1) 17–37.Google Scholar
Forgy, C and McDermott, J, 1976, “OPS, a domain-independent production system language” In: Proceedings 5th International Joint Conference on Artificial Intelligence Cambridge, MA, 933–939.Google Scholar
Gardarin, G, de Maindreville, C and Simon, E, 1989, Extending a Relational DBMS Towards a Rule-Based System: An Approach Using Predicate Transition Nets pp 131–152, Springer-Verlag.Google Scholar
Gehani, N and Jagadish, HV, 1991, “Ode as an Active Database: Constraints and Triggers” In Camps Lohman, S, ed., Proceedings 17th VLDB Conference pp 327–336, Barcelona, 09.Google Scholar
Gehani, NH, Jagadish, HV and Shmueli, O, 1992, “Event Specification in an Active Object-Oriented Database” In: Proceedings ACM SIGMOD Int. Conf on Management of Data San Diego, CA,06.Google Scholar
Gehani, NH, Jagadish, HV and Shmueli, O, 1992-a, “Composite Event Specification in Active Databases: Model and Implementation” In: Proceedings 18th mt. Conf on Very Large Databases Vancouver, Canada, 08.Google Scholar
Hajnal, SJ, Fox, J and Krause, PJ, 1989, “Sceptic User manual” Technical Report Imperial Cancer Research Fund.Google Scholar
Hanson, EN, 1989, “An Initial report on the Design of Arid: A DBMS With an Integrated production Rule System” ACM SIGMOD Record 18(3) 10.CrossRefGoogle Scholar
Hanson, EN, 1992, “Rule Condition Testing and Action Execution in Arid” In: Proceedings ACM SIGMOD mt. Conf. on Management of Data San Diego, CA, 06.Google Scholar
Held, G, 1975, “INGRES: A Relational Data Base System” In: Proceedings National Computer Conference Anaheim, CA, 06.Google Scholar
Hellerstein, JM, 1991, “Determinism in Partially Ordered Production Systems” IBM research report.Google Scholar
Ingres Corporation, Introducing INGRES Release 6.4”Google Scholar
lyengar, SS, Sabharwal, A, Pin, FG and Weisbin, CR, 1992, “Asynchronous production system for control of an autonomous mobile robot in real-time environment” Applied Artificial Intelligence 6(4) 485–510.Google Scholar
Kiernan, G, Maindrcville, C and Simon, E, 1987, “A Production Rule Language for Databases extended towards the Support of Complex Domains” Technical Report N-1133 INRIA, Rocquencourt, France.Google Scholar
Kiernan, O, Maindrcville, C and Simon, E, 1990, “Making a Deductive Database a Practical Technology: a step forward” In: Garcia-Molin, H and Jagadish, HV eds., Proceedings ACM Conference on the Management of Data (SIGMOD) pp 237–246, Atlantic City, 05.Google Scholar
Kim, W, Lee, Y and Seo, J, 1992, “A Framework For Supporting Triggers in Object-Oriented Database Systems” Int. Journal of intelligent and Cooperative Information Systems 1(1) 127–143.Google Scholar
Laird, JE, Newell, A and Rosenbloom, PS, 1982, “SOAR: an architecture for general intelligence” Artificial intelligence 33(1).Google Scholar
Lohman, GM, Lindsay, B, Pirahesh, H and Schiefer, KB, 1991, “Extensions to Starburst: Objects, Types, Functions and Rules” Communications of the ACM 34(10) 94–109, 10.CrossRefGoogle Scholar
Markov, A, 1954, “Theory of Algorithms” National Academy of Sciences, USSR.Google Scholar
McCarthy, DR and Dayal, U, 1989, “The Architecture Of An Active Data Base Management System” In: Proceedings ACM SIGMOD Conference on Management of Data pp 215–224, Portland, OR, 06.Google Scholar
Meyfarth, R, 1991, “ACTROB: An Active Robotic Knowledge Base” In: 2ndlnternational Symposium on Database Systems for Advanced Applications pp 330–338, Tokyo, 04.Google Scholar
Newell, A, 1973, “Production systems: models of control structures” In: Chase, WG, ed., Visual Information processing Academic Press, 463–526.Google Scholar
Newell, A, 1991, Unified Theories of Cognition Harvard University Press.Google Scholar
Newell, A and McDermott, J, 1975, “PSG manual”. Department of Computer Science, Carnegie-Mellon University.Google Scholar
Newell, A and Simon, HA, 1972, Human Problem Solving Prentice-Hall.Google Scholar
Nii, HP and Feigenbaum, EA, 1978, “Rule based understanding of Signals” In: Waterman, DA and Hayes-Roth, F, eds., Pattern-Directed Inference Systems Academic Press.Google Scholar
Post, EL 1943, “Formal Reductions of the general combinatorial decision problem” American Journal of Mathematics 65: 197–268.Google Scholar
Rosenthal, A, Chakravarthy, S and Blaustein, B, 1989, “Situation Monitoring for Active Databases” In: Wiederhold, , ed., Proceedings 15th VLDB Conference pp 455–463, Amsterdam, 08.Google Scholar
Schreier, U, Pirahesh, H, Agrawal, R and Mohan, C, 1991, “Alert: An Architecture for Transforming a Passive DBMS into an Active DBMS” In: Camps Lohman, S., ed., Proceedings 17th VLDB Conference pp 469–477, Barcelona, 09.Google Scholar
Simon, E, Kiernan, J and Maindreville, C, 1992, “Implementing High Level Active Rules on top of a Relational DBMS” In: Yuan, , ed., Proceedings 18th VLDB Conference pp 315–326, Vancouver, Canada, 08.Google Scholar
Shortliffe, EH, 1976, Computer-based Medical Consultations: MYCIN Elsevier.Google Scholar
Stonebrake, M, Hanson, EN and Potamianos, S, 1988, “The POSTGRES Rule Manager” IEEE Trans. Software Engineering 14(7) 897–907, 07.Google Scholar
Stonebraker, M and Jhingran, A, 1990, “On Rules, Procedures, Caching and Views in Data Base Systems” In Garcia-Molina, H and Jagadish, HV, eds., Proceedings ACM Conference on the Management of Data (SIGMOD) pp 281–290, Atlantic City, 05.Google Scholar
Stoncbrakcr, M, Rowe, LA and Hirohama, M, 1989, “The Implementation of Postgres” Technical report, University of California, Berkeley.Google Scholar
Vaghani, J, Ramamohanarao, K, Kemp, D, Somogyi, Z and Stuckey, P, 1990, “Design overview of the Aditi deductive database system” In: Proceedings NACLP Workshop on Deductive Databases Kansas State University.Google Scholar
Vere, SA, 1978, “Inductive learning of relational production systems” In: Waterman, DA and Hayes-Roth, F, eds., Pattern-Directed Inference Systems Academic Press.Google Scholar
Vicille, L, Bayer, P, Küchenhoff, V, Lefebvre, A and Manthey, R, 1991, “An Overview of the EKS-VI System” TR-KB-38, ECRC, August.Google Scholar
Waterman, DA and Hayes-Roth, F, 1978, Pattern-Directed inference Systems Academic Press.Google Scholar
Widom, J, Cochrane, RJ and Lindsay, BG, 1991, “Implementing Set-Oriented Production Rules as an Extension to Starburst” In: Camps, Lohman S, ed., Proceedings 17th VLDB Conference pp 275–285, Barcelona, 09.Google Scholar
Widorn, J and Finkelstein, SJ, 1990, “Set-Oriented Production Rules in Relational Database Systems” ACM Trans. Database Systems 259–270.CrossRefGoogle Scholar
Zhou, Y and Hsu, M, 1990, “A Theory for Rule Triggering Systems” In: Bancilhon, F, Thanos, C and Tsichritzis, , eds., Proceedings 2nd International Conference on Extending Database Technology (EDBT 90) pp 407–421, Venice, Italy, 03.Google Scholar