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: 1.2.1
Imports: Rcpp (≥ 0.12.5), DiceKriging, GPareto, KrigInv, DiceDesign, MASS, mnormt, mvtnorm, methods, matrixStats
LinkingTo: Rcpp
Suggests: DiceOptim, testthat
Published: 2025-11-14
DOI: 10.32614/CRAN.package.GPGame
Author: Victor Picheny ORCID iD [aut], Mickael Binois ORCID iD [aut, cre]
Maintainer: Mickael Binois <mickael.binois at inria.fr>
BugReports: https://github.com/vpicheny/GPGame/issues
License: GPL-3
URL: https://github.com/vpicheny/GPGame
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: GPGame results

Documentation:

Reference manual: GPGame.html , GPGame.pdf

Downloads:

Package source: GPGame_1.2.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): GPGame_1.2.1.tgz, r-oldrel (x86_64): GPGame_1.2.1.tgz
Old sources: GPGame archive

Linking:

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