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https://doi.org/10.2139/ssrn.4...
Article . 2024 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2023
License: arXiv Non-Exclusive Distribution
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Nonparametric Strategy Test

Authors: Sam Ganzfried;

Nonparametric Strategy Test

Abstract

We present a nonparametric statistical test for determining whether an agent is following a given mixed strategy in a repeated strategic-form game given samples of the agent's play. This involves two components: determining whether the agent's frequencies of pure strategies are sufficiently close to the target frequencies, and determining whether the pure strategies selected are independent between different game iterations. Our integrated test involves applying a chi-squared goodness of fit test for the first component and a generalized Wald-Wolfowitz runs test for the second component. The results from both tests are combined using Bonferroni correction to produce a complete test for a given significance level alpha. We applied the test to publicly available data of human rock-paper-scissors play. The data consists of 50 iterations of play for 500 human players. We test with a null hypothesis that the players are following a uniform random strategy independently at each game iteration. Using a significance level of alpha = 0.05, we conclude that 305 (61%) of the subjects are following the target strategy.

Keywords

game theory, FOS: Computer and information sciences, Technology, Computer Science - Artificial Intelligence, T, QA75.5-76.95, Methodology (stat.ME), FOS: Economics and business, nonparametric statistics, Artificial Intelligence (cs.AI), Computer Science - Computer Science and Game Theory, Electronic computers. Computer science, Economics - Theoretical Economics, Theoretical Economics (econ.TH), Computer Science - Multiagent Systems, Statistics - Methodology, Computer Science and Game Theory (cs.GT), Multiagent Systems (cs.MA)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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