GPGame: Solving Complex Game Problems using Gaussian Processes

Sequential strategies for finding a game equilibrium are proposed in a black-box setting (expensive pay-off evaluations, no derivatives). The algorithm handles noiseless or noisy evaluations. Two acquisition functions are available. Graphical outputs can be generated automatically. V. Picheny, M. Binois, A. Habbal (2018) <doi:10.1007/s10898-018-0688-0>. M. Binois, V. Picheny, P. Taillandier, A. Habbal (2020) <doi:10.48550/arXiv.1902.06565>.

Version: 1.2.0
Imports: Rcpp (≥ 0.12.5), DiceKriging, GPareto, KrigInv, DiceDesign, MASS, mnormt, mvtnorm, methods, matrixStats
LinkingTo: Rcpp
Suggests: DiceOptim, testthat
Published: 2022-01-23
DOI: 10.32614/CRAN.package.GPGame
Author: Victor Picheny ORCID iD [aut, cre], Mickael Binois [aut]
Maintainer: Victor Picheny <victor.picheny at>
License: GPL-3
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: GPGame results


Reference manual: GPGame.pdf


Package source: GPGame_1.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): GPGame_1.2.0.tgz, r-oldrel (arm64): GPGame_1.2.0.tgz, r-release (x86_64): GPGame_1.2.0.tgz, r-oldrel (x86_64): GPGame_1.2.0.tgz
Old sources: GPGame archive


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