Learning to Design Games: Strategic Environments in Reinforcement Learning

5 Jul 2017Haifeng ZhangJun WangZhiming ZhouWeinan ZhangYing WenYong YuWenxin Li

In typical reinforcement learning (RL), the environment is assumed given and the goal of the learning is to identify an optimal policy for the agent taking actions through its interactions with the environment. In this paper, we extend this setting by considering the environment is not given, but controllable and learnable through its interaction with the agent at the same time... (read more)

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