From 385abe0369fb76b71915ea8c6ba4981d0952dd7d Mon Sep 17 00:00:00 2001 From: Andrej Orsula Date: Tue, 4 Jun 2024 11:46:57 +0200 Subject: [PATCH] Update link to the report Signed-off-by: Andrej Orsula --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 53d2c09..9fba5d6 100644 --- a/README.md +++ b/README.md @@ -12,7 +12,7 @@ https://github.com/AndrejOrsula/drl_air_hockey/assets/22929099/68b39c9c-2d18-4ea The implemented approach focuses on applying a model-based deep reinforcement learning algorithm [DreamerV3](https://danijar.com/project/dreamerv3) to acquire a policy capable of playing air hockey with continuous observations and actions. -- Additional details about the approach are presented in the report [here](https://www.ias.informatik.tu-darmstadt.de/uploads/Team/PuzeLiu/AirHockeyChallenge_SpaceR.pdf). +- Additional details about the approach are presented in the report [here](https://arxiv.org/pdf/2406.00518). - Models of pre-trained agents can be downloaded from [here](https://drive.google.com/drive/folders/1bfj0VCm7wbGKBh5i_-Oso3XCcJbNZ_8E). ## Instructions