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A Framework for Integrating Heterogeneous Learning Agents

  • Conference paper
Second Generation Expert Systems

Abstract

Machine Learning is a rapidly growing subfield of Artificial Intelligence, and a large variety of learning algorithms have been reported in the literature. However, no one algorithm provides a totally satisfactory solution to a wide range of problems.

This chapter describes our domain-independent Integrated Learning System (ILS), and one application, which learns how to control a telecommunications network. Our approach includes a framework for combining various learning paradigms, integrating different reasoning techniques, and coordinating distributed cooperating problem-solvers.

The current implementation has five learning paradigms (agents) that cooperate to improve problem-solving performance. ILS also includes a central controller, called The Learning Coordinator (TLC), which manages control flow and communication between the agents. The agents provide TLC with advice. TLC chooses which suggestion to adopt and performs the appropriate actions. At intervals, the agents can inspect the results of the TLC’s actions and use this feedback to learn, improving the value of their future advice.

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Author information

Authors and Affiliations

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

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

Authors
  1. Bernard Silver
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  2. John Vittal
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  3. William Frawley
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  4. Glenn Iba
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  5. Tom Fawcett
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  6. Susan Dusseault
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  7. John Doleac
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Editor information

Editors and Affiliations

  1. Service Systèmes Experts, Renault, 860 Quai Stalingrad, 92109, Boulogne-Billancourt, France

    Jean-Marc David

  2. Direction des Etudes et Recherches, Electricité de France, 1, Av. du Général de Gaulle, 92141, Clamart Cedex, France

    Jean-Paul Krivine

  3. School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213-3890, USA

    Reid Simmons

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© 1993 Springer-Verlag Berlin Heidelberg

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Silver, B. et al. (1993). A Framework for Integrating Heterogeneous Learning Agents. In: David, JM., Krivine, JP., Simmons, R. (eds) Second Generation Expert Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77927-5_31

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  • DOI: https://doi.org/10.1007/978-3-642-77927-5_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-77929-9

  • Online ISBN: 978-3-642-77927-5

  • eBook Packages: Springer Book Archive

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