We derive a ‘high probability’ concentration bound for stochastic approximation schemes for finding the fixed point of a contraction map, and illustrate its applications in reinforcement learning for approximate dynamic programming.

中文翻译：

---

收缩随机逼近的浓度

我们推导了随机近似方案的“高概率”集中度，用于找到收缩图的固定点，并举例说明了其在强化学习中用于近似动态规划的应用。