Reinforcement Learning

Reinforcement learning is a framing of enabling agents to learn by trial and error from interaction with environments. Reinforcement learning has some problems, for example, the delay of the evaluation (reward) for agent’s action, the long learning time, and the trade-off between exploration and exploitation. We research methods for solving these problems.