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International Conference on Computational Learning Theory

COLT 2005: Learning Theory pp 233–248Cite as

Competitive Collaborative Learning

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3559))

Abstract

We develop algorithms for a community of users to make decisions about selecting products or resources, in a model characterized by two key features:

  • The quality of the products or resources may vary over time.

  • Some of the users in the system may be dishonest, manipulating their actions in a Byzantine manner to achieve other goals.

We formulate such learning tasks as an algorithmic problem based on the multi-armed bandit problem, but with a set of users (as opposed to a single user), of whom a constant fraction are honest and are partitioned into coalitions such that the users in a coalition perceive the same expected quality if they sample the same resource at the same time. Our main result exhibits an algorithm for this problem which converges in polylogarithmic time to a state in which the average regret (per honest user) is an arbitrarily small constant.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA

    Baruch Awerbuch

  2. Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA

    Robert D. Kleinberg

Authors
  1. Baruch Awerbuch
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  2. Robert D. Kleinberg
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Editor information

Editors and Affiliations

  1. University of Leoben, A-8700, Leoben, Austria

    Peter Auer

  2. Department of Electrical Engineering, Technion, P.O. Box, 3200, Haifa, Israel

    Ron Meir

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© 2005 Springer-Verlag Berlin Heidelberg

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Awerbuch, B., Kleinberg, R.D. (2005). Competitive Collaborative Learning. In: Auer, P., Meir, R. (eds) Learning Theory. COLT 2005. Lecture Notes in Computer Science(), vol 3559. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11503415_16

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  • DOI: https://doi.org/10.1007/11503415_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26556-6

  • Online ISBN: 978-3-540-31892-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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