From cb17ff6a7c0982f5d9077bb669ac21d08c527202 Mon Sep 17 00:00:00 2001 From: qiwang067 Date: Sat, 4 Jul 2020 15:34:17 +0800 Subject: [PATCH] change readme --- README.md | 12 ++++++------ docs/README.md | 12 ++++++------ 2 files changed, 12 insertions(+), 12 deletions(-) diff --git a/README.md b/README.md index 5d8cc23..6348c95 100644 --- a/README.md +++ b/README.md @@ -10,14 +10,14 @@ - bilibili：[李宏毅《深度强化学习》](https://www.bilibili.com/video/BV1MW411w79n) ## 目录 -- [P1 Policy Gradient](https://datawhalechina.github.io/leedeeprl-notes/#/chapter1/chapter1) +- [P1 策略梯度](https://datawhalechina.github.io/leedeeprl-notes/#/chapter1/chapter1) - [P2 Proximal Policy Optimization (PPO)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter2/chapter2) -- [P3 Q-learning (Basic Idea)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter3/chapter3) -- [P4 Q-learning (Advanced Tips)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter4/chapter4) -- [P5 Q-learning (Continuous Action)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter5/chapter5) +- [P3 Q-learning (基本概念)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter3/chapter3) +- [P4 Q-learning (进阶技巧)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter4/chapter4) +- [P5 Q-learning (连续行动)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter5/chapter5) - [P6 Actor-Critic](https://datawhalechina.github.io/leedeeprl-notes/#/chapter6/chapter6) -- [P7 Sparse Reward](https://datawhalechina.github.io/leedeeprl-notes/#/chapter7/chapter7) -- [P8 Imitation Learning](https://datawhalechina.github.io/leedeeprl-notes/#/chapter8/chapter8) +- [P7 稀疏奖励](https://datawhalechina.github.io/leedeeprl-notes/#/chapter7/chapter7) +- [P8 模仿学习](https://datawhalechina.github.io/leedeeprl-notes/#/chapter8/chapter8) ## 主要贡献者 diff --git a/docs/README.md b/docs/README.md index f7c1bd2..434b3b1 100644 --- a/docs/README.md +++ b/docs/README.md @@ -7,14 +7,14 @@ - bilibili：[李宏毅《深度强化学习》](https://www.bilibili.com/video/BV1MW411w79n) ## 目录 -- [P1 Policy Gradient](https://datawhalechina.github.io/leedeeprl-notes/#/chapter1/chapter1) +- [P1 策略梯度](https://datawhalechina.github.io/leedeeprl-notes/#/chapter1/chapter1) - [P2 Proximal Policy Optimization (PPO)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter2/chapter2) -- [P3 Q-learning (Basic Idea)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter3/chapter3) -- [P4 Q-learning (Advanced Tips)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter4/chapter4) -- [P5 Q-learning (Continuous Action)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter5/chapter5) +- [P3 Q-learning (基本概念)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter3/chapter3) +- [P4 Q-learning (进阶技巧)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter4/chapter4) +- [P5 Q-learning (连续行动)](https://datawhalechina.github.io/leedeeprl-notes/#/chapter5/chapter5) - [P6 Actor-Critic](https://datawhalechina.github.io/leedeeprl-notes/#/chapter6/chapter6) -- [P7 Sparse Reward](https://datawhalechina.github.io/leedeeprl-notes/#/chapter7/chapter7) -- [P8 Imitation Learning](https://datawhalechina.github.io/leedeeprl-notes/#/chapter8/chapter8) +- [P7 稀疏奖励](https://datawhalechina.github.io/leedeeprl-notes/#/chapter7/chapter7) +- [P8 模仿学习](https://datawhalechina.github.io/leedeeprl-notes/#/chapter8/chapter8) ## 主要贡献者