Heuristics in experiments with infinitely large strategy spaces
We introduce a new methodology that enables detection of the onset of convergence towards Nash equilibria in simple repeated games with infinitely large strategy spaces, thereby revealing the heuristics used in decision-making. The method works by constraining on a special finite subset of strategie...
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Veröffentlicht in: | arXiv.org 2020-05 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | We introduce a new methodology that enables detection of the onset of convergence towards Nash equilibria in simple repeated games with infinitely large strategy spaces, thereby revealing the heuristics used in decision-making. The method works by constraining on a special finite subset of strategies, called decoupled strategies. We show how the technique can be applied to understand price formation in financial market experiments by introducing a predictive measure {\Delta}D: the different between positive decoupled strategies (recommending to buy) and negative decoupled strategies (recommending to sell). Using {\Delta}D we illustrate how the method can predict (at certain special times) participants' actions with a high success rate in a series of experiments |
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ISSN: | 2331-8422 |
DOI: | 10.48550/arxiv.2005.02337 |