Dataset with 200 million 3-by-3 strategic games for comparing Perfectly Transparent Equilibria with Nash Equilibria

Fourny, Ghislain; Sulser Larraz, Felipe

doi:10.3929/ethz-b-000444921

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dc.contributor.author

Fourny, Ghislain

dc.contributor.author

Sulser Larraz, Felipe

dc.date.accessioned

2020-10-08T06:34:56Z

dc.date.available

2020-10-07T14:04:35Z

dc.date.available

2020-10-08T06:34:56Z

dc.date.created

2020-10-31/2020-02-19

en_US

dc.date.issued

2020-10-07

dc.identifier.uri

http://hdl.handle.net/20.500.11850/444921

dc.identifier.doi

10.3929/ethz-b-000444921

dc.description.abstract

This dataset contains 200 million games in normal form played by two agents with each strategies, and in general position. The Nash Equilibria and Perfectly Transparent Equilibria are pre-computed.

en_US

dc.format

application/zip

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dc.format

text/csv

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dc.format

text/plain

en_US

dc.format

text/csv

en_US

dc.language.iso

en

en_US

dc.publisher

ETH Zurich, Institute for Computing Platforms

en_US

dc.rights.uri

http://rightsstatements.org/page/InC-NC/1.0/

dc.subject

Game theory

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dc.subject

GAME THEORY (MATHEMATICS)

en_US

dc.subject

Strategic games

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dc.subject

NASH EQUILIBRIUM (GAME THEORY)

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dc.subject

Nash equilibrium

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dc.subject

Perfect Prediction

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dc.title

Dataset with 200 million 3-by-3 strategic games for comparing Perfectly Transparent Equilibria with Nash Equilibria

en_US

dc.type

Dataset

dc.rights.license

In Copyright - Non-Commercial Use Permitted

dc.date.published

2020-10-08

ethz.size

4.13 GB

en_US

ethz.date.collected

2020-10-31/2020-02-19

en_US

ethz.code.ddc

DDC - DDC::3 - Social sciences::330 - Economics

en_US

ethz.code.jel

JEL - JEL::C - Mathematical and Quantitative Methods::C7 - Game Theory and Bargaining Theory::C72 - Noncooperative Games

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ethz.notes

The data is organized in 100 shards, 20 per zip file, so that it is also possible to analyze smaller samples.

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ethz.geolocation.placename

Zurich

ethz.publication.place

Zurich

en_US

ethz.leitzahl

ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02663 - Institut für Computing Platforms / Institute for Computing Platforms::03506 - Alonso, Gustavo / Alonso, Gustavo

en_US

ethz.leitzahl.certified

ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science::02663 - Institut für Computing Platforms / Institute for Computing Platforms::03506 - Alonso, Gustavo / Alonso, Gustavo

en_US

ethz.date.retentionend

indefinite

en_US

ethz.date.retentionendDate

n/a

ethz.date.deposited

2020-10-07T14:04:49Z

ethz.source

FORM

ethz.eth

yes

en_US

ethz.availability

Open access

en_US

ethz.description.methods

The games were automatically generated by taking random payoff permutations on the integers 0-8 for each game and agent. It is thus a simple random sample with replacement. The game matrix is in field y as a three-dimensional array of payoffs: two dimensions for each player's choice of strategy, one dimension for the player receiving this payoff. The Nash equilibrium (field N) and the Perfectly Transparent Equilibrium (field P) are pre-computed. The equilibrium fields contain an array of coordinates (starting at 0) of the equilibria in the matrix in field y, not the payoffs. There are 5 zip files, each containing 20 text files in the JSON Lines format, each containing around 2 million objects. The CSV file contains the results of an analysis of the dataset with the existence ratios of a Nash equilibrium (N), a unique Nash equilibrium (NU) and the Perfectly Transparent Equillibrium (PTE). The code that produced the JSON dataset was written in Python. The code that produced the CSV intermediate results was written in JSONiq.

en_US

ethz.description.software

Spark Python/PySpark JSONiq/Rumble

en_US

ethz.rosetta.installDate

2020-10-08T06:37:10Z

ethz.rosetta.lastUpdated

2024-02-02T12:16:20Z

ethz.rosetta.versionExported

true

ethz.COinS

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