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dc.contributor.author
Fourny, Ghislain
dc.contributor.author
Sulser Larraz, Felipe
dc.date.accessioned
2020-10-08T07:28:13Z
dc.date.available
2020-10-07T14:43:27Z
dc.date.available
2020-10-08T06:13:18Z
dc.date.available
2020-10-08T07:28:13Z
dc.date.created
2020-10-31/2020-02-19
en_US
dc.date.issued
2020-10-07
dc.identifier.uri
http://hdl.handle.net/20.500.11850/444956
dc.identifier.doi
10.3929/ethz-b-000444956
dc.description.abstract
This dataset contains 100,000 games in normal form played by four agents with each three strategies, and in general position. The Nash Equilibria and Perfectly Transparent Equilibria are pre-computed.
en_US
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
en_US
dc.subject
GAME THEORY (MATHEMATICS)
en_US
dc.subject
Strategic games
en_US
dc.subject
NASH EQUILIBRIUM (GAME THEORY)
en_US
dc.subject
Nash equilibrium
en_US
dc.subject
Perfect Prediction
en_US
dc.title
Dataset with 100,000 3x3x3x3 strategic games for comparing the social utility of Perfectly Transparent Equilibria with that of Nash Equilibria
en_US
dc.type
Dataset
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2020-10-08
ethz.size
132.46 MB
en_US
ethz.date.collected
2020-10-31/2020-02-19
en_US
ethz.notes
The data is organized in 8 shards, with 12,500 JSON objects per file, so that it is also possible to analyze smaller samples.
en_US
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.date.retentionend
indefinite
en_US
ethz.date.retentionendDate
n/a
ethz.date.deposited
2020-10-07T14:43:38Z
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 0-80 for each game and agent. It is thus a simple random sample with replacement. The game matrix is in field y as a five-dimensional array of payoffs: four 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 8 JSON Lines files, each containing around 12,000 or 13,000 objects. The CSV file contains the results of an analysis of the dataset with the distribution of social utilities (Thiel-L function) for the unique Nash equilibrium and the Perfectly Transparent Equillibrium. 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
2020-10-08T06:13:39Z
ethz.rosetta.lastUpdated
2021-02-15T17:55:28Z
ethz.rosetta.versionExported
true
ethz.COinS
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