Variance Decompositions for Extensive-Form Games

@article{Cloud2021VarianceDF,
  title={Variance Decompositions for Extensive-Form Games},
  author={Alex Cloud and Eric Laber},
  journal={2021 IEEE Conference on Games (CoG)},
  year={2021},
  pages={1-8}
}
  • Alex CloudE. Laber
  • Published 8 September 2020
  • Economics
  • 2021 IEEE Conference on Games (CoG)
The extent to which an individual or chance can influence the outcome of a game is a central question in the analysis of games. Consequently, the ability to characterize sources of variation in game outcomes may have significant implications in areas such as game design, law, and multi-agent reinforcement learning. We derive a closed-form expression and estimators for the variance in the outcome of a general multi-agent game that is attributable to a player or chance. We analyze poker hands to… 

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