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Rage Against the Machines: How Subjects Learn to Play Against Computers

  • Peter Dürsch

    ()

    (University of Heidelberg, Department of Economics)

  • Albert Kolb

    (University of Bonn, Department of Economics)

  • Jörg Oechssler

    ()

    (University of Heidelberg, Department of Economics)

  • Burkhard C. Schipper

    ()

    (University of California, Department of Economics)

We use an experiment to explore how subjects learn to play against computers which are programmed to follow one of a number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious play, imitation, reinforcement learning, and a trial & error process. We test whether subjects try to influence those algorithms to their advantage in a forward-looking way (strategic teaching). We find that strategic teaching occurs frequently and that all learning algorithms are subject to exploitation with the notable exception of imitation. The experiment was conducted, both, on the internet and in the usual laboratory setting. We find some systematic differences, which however can be traced to the different incentives structures rather than the experimental environment.

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File URL: http://www.uni-heidelberg.de/md/awi/forschung/dp423.pdf
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Paper provided by University of Heidelberg, Department of Economics in its series Working Papers with number 0423.

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Length: 43 pages
Date of creation: Oct 2005
Date of revision: Oct 2005
Handle: RePEc:awi:wpaper:0423
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