Figure Data for the paper "Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning"
Julien Pérolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub, de Boer, Vincent, Paul Friedrich Müller, Jerome T. Connor, NEIL R. BURCH, Anthony, Thomas, Stephen McAleer, Romuald Élie, Sarah H. Cen, Zhe Wang, Audrūnas Gruslys, Aleksandra Malysheva, Mina Khan, Sherjil Ozair, Finbarr Timbers, Toby Pohlen · Zenodo (CERN European Organization for Nuclear Research) · 2022
Data Release for Article: Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning This package releases a Python notebook reproducing the quantitative figures featured in the research article "Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning". Usage The notebook can be uploaded to and executed using the [Colab](https://colab.research.google.com) runtime service. The Python notebook is tested against Python `3.7`. License and disclaimer Copyright 2022 DeepMind Technologies Limited All software is licensed under the Apache License, Version 2.0 (Apache 2.0); you may not use this file except in compliance with the Apache 2.0 license. You may obtain a copy of the Apache 2.0 license at: https://www.apache.org/licenses/LICENSE-2.0 All other materials are licensed under the Creative Commons Attribution 4.0 International License (CC-BY). You may obtain a copy of the CC-BY license at: https://creativecommons.org/licenses/by/4.0/legalcode Unless required by applicable law or agreed to in writing, all software and materials distributed here under the Apache 2.0 or CC-BY licenses are distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the licenses for the specific language governing permissions and limitations under those licenses. This is not an official Google product.