1 – Introduction

For this lesson, we’ll confine our attention to a problem that’s slightly easier than the reinforcement learning problem. Instead of working in a setting where the agent has to learn from interaction, we’ll assume that the agent already knows everything about the environment. So the agent knows how the environment decides the next state, and it knows how the environment decides reward. The goal will remain the same. Given this information, the agent would like to find the optimal policy. Solving the simpler problem first will prove incredibly useful for building intuition before we tackle the full reinforcement learning problem. With this in mind, I’ll catch you in the next video.

%d 블로거가 이것을 좋아합니다: