---
sidebar_position: 12
tags: [AI, ML, RL]
---

# Reinforcement Learning

## Foundations

- [Markov Decision Process](./mdp.md) - 状态、动作、策略、奖励、回报、马尔可夫决策过程
- [Bellman Equation](./bellman.md) - 贝尔曼公式
- [Bellman Optimality Equation](./optimal.md) - 贝尔曼最优公式
- [Iteration](./iteration.md) - 值迭代、策略迭代、截断策略迭代

## Algorithms

- [Monte Carlo](./monte-carlo.md) - 蒙特卡洛学习
- [Stochastic Approximation](./stochastic-approximation.md) - 随机梯度下降
- [Temporal-Difference](./temporal-difference.md) - TD 学习与 Q-learning
- [Value Function Approximation](./value-function.md) - 值函数逼近
- [Policy Gradient](./policy-gradient.md) - 策略梯度算法
- [Actor-Critic](./actor-critic.md) - Actor-Critic 算法
