Adaptive choice of information sources

Extended abstract
  • Sandip Sen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1435)


We present a number of learning approaches by which agents can adapt to select information sources that satisfy performance requirements. Performance can be interpreted both in terms of the quality of information provided by the sources, as well as the response time to process information requests. We first present a couple of approaches by which self-motivated agents can learn to choose lightly-loaded resources. The resultant load balancing effect results in increasing throughput for the entire system as well as faster response times for individual agents. We also present an expected utility maximization approach to selecting information sources that are likely to deliver better quality information to different classes of queries.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Sandip Sen
    • 1
  1. 1.Department of Mathematical & Computer SciencesUniversity of TulsaTulsa

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