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

Peter Dürsch, Albert Kolb, Jörg Oechssler and Burkhard Schipper ()

No 31/2005, Bonn Econ Discussion Papers from University of Bonn, Bonn Graduate School of Economics (BGSE)

Abstract: 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

Keywords: learning; fictitious play; imitation; reinforcement . trial & error; strategic teaching; Cournot duopoly; experiments; internet (search for similar items in EconPapers)
JEL-codes: D43 L13 C72 C92 C91 (search for similar items in EconPapers)
Date: 2005
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Related works:
Working Paper: Rage Against the Machines: How Subjects Learn to Play Against Computers (2005) Downloads
Working Paper: Rage Against the Machines: How Subjects Learn to Play Against Computers (2005) Downloads
Working Paper: Rage against the machines: how subjects learn to play against computers (2005) Downloads
Working Paper: Rage Against the Machines: How Subjects Learn to Play Against Computers (2005) Downloads
Working Paper: Rage Against the Machines: How Subjects Learn to Play Against Computers (2005) Downloads
Working Paper: Rage Against the Machines - How Subjects Learn to Play Against Computers (2005) Downloads
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