Skip to main content
SpringerLink
Log in

A framework for cooperative adaptable information systems

  • Conference paper
  • First Online:
The Next Generation of Information Systems: From Data to Knowledge (IJCAI 1991)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 611))

Included in the following conference series:

  • 158 Accesses

Abstract

Both information systems and systems that automate complex control processes need to be able to adapt to new and possibly surprising situations, preferably without human intervention. These systems may not only need to control a domain, but also should be able to improve their own performance over time.

This paper describes the initial implementation of a domain-independent Integrated Learning System (Ils), and one application, which, through its own experience, learns how to control the traffic in a telephone network. The issues involve coordinating distributed cooperating heterogeneous problem-solvers, combining various learning paradigms, and integrating different reasoning techniques.

The Ils is a framework for integrating several heterogeneous learning agents that are written in different languages and run on different platforms; they cooperate to improve problem-solving performance. Ils also includes a central controller, called The Learning Coordinator (Tlc), which manages the control of flow and communication among the agents using a high-level communication protocol. The agents provide Tlc with expert advice. Tlc chooses which suggestion to adopt and performs the appropriate controls. At intervals, the agents can inspect the results of Tlc's actions and use this feedback to learn, improving the quality of their future advice.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Brandau, R., Lemmon, A. and Lafond, C. Experience with Extended Episodes: Cases with Complex Temporal Stucture. In Bareiss, R. (editor), Proceedings of 1991 DARPA Workshop on Case-Based Reasoning. DARPA, Morgan Kaufmann, 1991.

    Google Scholar 

  2. Chipalkatti, R., Kheradpir, S. and Stinson, W. NEMACS: The NEtwork MAnagement and Control Simulator. Technical Memorandum TM 0299-08-90-465-01, GTE Laboratories Incorporated, August, 1990.

    Google Scholar 

  3. Cormen, T.H., Leiserson, C.E. and Rivest, R.L. Introduction to Algorithms. MIT Press, 1990, Chapter 14.

    Google Scholar 

  4. DeJong, G. and Mooney, R. Explanation-Based Learning: An Alternative View. Machine Learning 1(2):145–176, 1986.

    Google Scholar 

  5. Fawcett, T.E. and Utgoff, P.E. A hybrid method for feature generation. In Birnbaum, L.A. and Collins, G.C. (editors), Proceedings of the Eighth International Workshop on Machine Learning, pages 137–141. 1991.

    Google Scholar 

  6. Fawcett, T.E. and Utgoff, P.E. Automatic feature generation for problem solving systems. COINS Technical Report 92-9, Dept of Computer and Information Science, Univ. of Massachusetts at Amherst, 1992.

    Google Scholar 

  7. Frawley, W.J. Using Functions to Encode Domain and Contextual Knowledge in Statistical Induction. In Piatetsky-Shapiro, G. and Frawley, W.J. (editors), Knowledge Discovery in Databases. AAAI Press, 1991.

    Google Scholar 

  8. Frawley, W.J., Fawcett, T.E. and Bradford, K. NETSIM: An object-oriented simulation of the operation and control of a circuit-switched network. Technical Report TN 88-506.1, Computer and Intelligent Systems Laboratory, GTE Laboratories Incorporated, 1988.

    Google Scholar 

  9. Iba, G.A. A Heuristic Approach to the Discovery of Macro-operators. Machine Learning 3(4):285–317, 1989.

    Google Scholar 

  10. Kosieniak, P., Mathis, V., St Jaques, M. and Stevens, D. The Network Control Assistant (NCA), a Real-time Prototype Expert System for Network Management. In Proceedings of First International Conference on Industrial & Engineering Applications of Artificial Intelligence and Expert Systems, pages 367–377. Association for Computing Machinery, 1988.

    Google Scholar 

  11. Matheus, C.J. and Rendell, L.A. Constructive Induction on Decision Trees. In Sridharan, N.S. (editor), Proceedings of the Eleventh IJCAI, pages 645-650. International Joint Conference on Artificial Intelligence, Morgan Kaufmann, 1989.

    Google Scholar 

  12. Mitchell, T.M., Keller, R.M. and Kedar-Cabelli, S.T. Explanation-Based Generalization: A Unifying View. Machine Learning 1(1):47–80, 1986.

    Google Scholar 

  13. Pagallo, G. and Haussler, D. Boolean Feature Discovery in Empirical Learning. Machine Learning 5(1):71–99, 1990.

    Google Scholar 

  14. Quinlan, J.R. Induction of Decision Trees. Machine Learning 1(1):81–106, 1986.

    Google Scholar 

  15. Silver, B. A Hybrid Approach in an Imperfect Domain. In DeJong, G. (editor), Proceedings of AAAI Symposium on Explanation-Based Learning. American Association for Artificial Intelligence, 1988.

    Google Scholar 

  16. Silver, B. NetMan: A Learning Network Traffic Controller. In Matthews, M. (editor), Proceedings of Third International Conference on Industrial & Engineering Applications of Artificial Intelligence and Expert Systems, pages 923–931. Association for Computing Machinery, 1990.

    Google Scholar 

  17. Silver, B., Vittal, J., Frawley, W., Iba, G. and Bradford, K. ILS: A Framework for Integrating Multiple Heterogeneous Learning Agents. In David, J-M. (editor), Procs of Second Generation Expert Systems, 10th International Workshop on Expert Systems and Their Applications, pages 301–313. 1990.

    Google Scholar 

  18. Silver, B., Frawley, W., Iba, G., Vittal, J. and Bradford, K. ILS: A Framework for Multi-Paradigmatic Learning. In Porter, B. and Mooney, R. (editors), Proceedings of the Seventh International Conference on Machine Learning, pages 348–356. Morgan Kaufmann, 1990.

    Google Scholar 

  19. Sutton, R.S. Integrated Architectures for Learning, Planning, and Reacting Based on Approximating Dynamic Programming. In Porter, B. and Mooney, R. (editors), Proceedings of the Seventh International Conference on Machine Learning, pages 216–224. Morgan Kaufmann, 1990.

    Google Scholar 

  20. Weihmayer, R., Brandau, R., and Shinn, H. Modes of Diversity: Issues in Cooperation Among Dissimilar Agents. In Huhns, M. (editor), Procs. of 10th Workshop on Distributed Artificial Intelligence. American Association for Artificial Intelligence, 1990.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. GTE Laboratories Incorporated, 40 Sylvan Road, 02254, Waltham, MA, USA

    John Vittal, Bernard Silver, William Frawley, Glenn Iba, Tom Fawcett, Susan Dusseault & John Doleac

Authors
  1. John Vittal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bernard Silver
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. William Frawley
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Glenn Iba
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tom Fawcett
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Susan Dusseault
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. John Doleac
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Michael P. Papazoglou John Zeleznikow

Rights and permissions

Reprints and permissions

Copyright information

© 1992 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Vittal, J. et al. (1992). A framework for cooperative adaptable information systems. In: Papazoglou, M.P., Zeleznikow, J. (eds) The Next Generation of Information Systems: From Data to Knowledge. IJCAI 1991. Lecture Notes in Computer Science, vol 611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55616-8_47

Download citation

  • DOI: https://doi.org/10.1007/3-540-55616-8_47

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-55616-9

  • Online ISBN: 978-3-540-47262-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation