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 [aut], Mickael Binois [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 |
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