Red-10 Game Environment

该数据集为红十卡牌游戏创建了一个环境，旨在评估交互式决策强化学习（IDRL）框架的性能。此外，该红十游戏环境还允许进行实验，以评估各种多代理强化学习（MARL）方法在与IDRL框架对比下的表现。该任务是在随机游戏设置中的多代理强化学习。

This dataset develops an environment for the Chinese Red Ten card game, aiming to evaluate the performance of the Interactive Decision-making Reinforcement Learning (IDRL) framework. Additionally, this Red Ten card game environment supports experiments to assess the performance of various multi-agent reinforcement learning (MARL) methods when compared against the IDRL framework. This task falls under the category of multi-agent reinforcement learning in stochastic game settings.