From 42e51e0653da7d5779e183c30f2f69bea20eb9e7 Mon Sep 17 00:00:00 2001 From: cedric Date: Tue, 31 Mar 2026 22:17:32 +0000 Subject: [PATCH] fix: clarified seperate policy and value network part --- docs/design_decisions/mlp_architecture.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/design_decisions/mlp_architecture.md b/docs/design_decisions/mlp_architecture.md index 0cdb381..045cf01 100644 --- a/docs/design_decisions/mlp_architecture.md +++ b/docs/design_decisions/mlp_architecture.md @@ -19,6 +19,6 @@ Inspired by: https://iclr-blog-track.github.io/2022/03/25/ppo-implementation-det For starters we will execute our tests with simple models. Each MLP will have only 1 hidden layer. This will be expanded as needed. The exceptions are the input networks / feature extractors — they will be given 2 hidden layers and 64 nodes per layer as advised in the blog. This might change as we make progress in our experiments. -Our policy and value networks use separate networks as advised by the paper and the blog. For continuous actions this should allow better learning at a small cost. +Our policy and value networks use separate input networks / feature extractors as advised by the SEL3 course assistants and the blog. For continuous actions this should allow better learning at a small cost. We use mean and log_std to represent the action distribution, because it is advised by previous research for learning stability and other reasons. \ No newline at end of file