From 87fcfeb9bbc8baeb579e2cf1ddd2fa2de804902c Mon Sep 17 00:00:00 2001 From: Balaji Varatharajan Date: Sat, 17 Feb 2024 15:16:29 +0530 Subject: [PATCH] Update variance-problem.mdx Hi, I've a blog titled [High Variance in Policy gradients](https://balajiai.github.io/high_variance_in_policy_gradients) which also explains about the variance problem in policy gradient and techniques for variance reduction such as baseline and actor-critics method. I think, it would be valuable to this course readers. So I'm adding it to the reading-list. Thanks! --- units/en/unit6/variance-problem.mdx | 1 + 1 file changed, 1 insertion(+) diff --git a/units/en/unit6/variance-problem.mdx b/units/en/unit6/variance-problem.mdx index 9ce3d8e..1fbbe9c 100644 --- a/units/en/unit6/variance-problem.mdx +++ b/units/en/unit6/variance-problem.mdx @@ -27,4 +27,5 @@ However, increasing the batch size significantly **reduces sample efficiency**. If you want to dive deeper into the question of variance and bias tradeoff in Deep Reinforcement Learning, you can check out these two articles: - [Making Sense of the Bias / Variance Trade-off in (Deep) Reinforcement Learning](https://blog.mlreview.com/making-sense-of-the-bias-variance-trade-off-in-deep-reinforcement-learning-79cf1e83d565) - [Bias-variance Tradeoff in Reinforcement Learning](https://www.endtoend.ai/blog/bias-variance-tradeoff-in-reinforcement-learning/) +- [High Variance in Policy gradients](https://balajiai.github.io/high_variance_in_policy_gradients) ---