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EEML 2012 – Experimental Economics in Machine Learning

Научный редактор: R. Tagiew, D. I. Ignatov, A. Neznanov, J. Poelmans.

In Experimental Economics, laboratory and f eld experiments are conducted on subjects in order to improve theoretical knowledge about human behavior in interactions. Although paying diff erent amounts of money restricts the preferences of the subjects in experiments, the exclusive application of analytical game theory does not suce to explain the recorded data. It exacts the development and evaluation of more sophisticated models. In some experiments, human subjects are involved into an interaction with automated agents and these agents are used for simulating human interactions. The more data is used for the evaluation, the more of statistical signi cance can be achieved. Since huge amounts of behavioral data are required to be scanned for regularities and automated agents are required to simulate and to intervene human interactions, Machine Learning is the tool of choice for the research in Experimental Economics. Moreover modern economics extensively involves network structures, which can be modeled as graphs or more complicated relational structures.

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EEML 2012 – Experimental Economics in Machine Learning