From 4d0938ded0051ba3c393054587f86ac6dd64b5c2 Mon Sep 17 00:00:00 2001 From: NM512 Date: Mon, 19 Jun 2023 06:02:35 +0900 Subject: [PATCH] updated README --- README.md | 27 ++++++++++++--------------- 1 file changed, 12 insertions(+), 15 deletions(-) diff --git a/README.md b/README.md index 3207938..ba7f552 100644 --- a/README.md +++ b/README.md @@ -17,25 +17,22 @@ tensorboard --logdir ./logdir ``` ## Benchmarks -So far, this repository allows testing the following benchmarks. -| Environment | Observation | Action | Description | -|-------------------|---|---|-----------------------| -| [DMC Proprio](https://github.com/deepmind/dm_control) | State | Continuous | This benchmark contains 18 continuous control tasks with low-dimensional inputs and a budget of 500K environment steps. | -| [DMC Vision](https://github.com/deepmind/dm_control) | Image | Continuous | This benchmark consists of 20 continuous control tasks where the agent receives only high-dimensional images as inputs and a budget of 1M environment steps. | -| [Atari 100k](https://github.com/openai/atari-py) | Image | Discrete | This benchmark includes 26 Atari games and a budget of only 400K environment steps, amounting to 100K steps after action repeat or 2 hours of real time. | -| [Crafter](https://github.com/danijar/crafter) | Image | Discrete | This survival environment evaluates diverse agent abilities, including exploration, reasoning, credit assignment, and generalization.| -| [Memory Maze](https://github.com/jurgisp/memory-maze) | Image | Discrete | Memory Maze is a 3D benchmark with randomized mazes to evaluate RL agents' long-term memory.| +So far, the following benchmarks can be used for testing. +| Environment | Observation | Action | Budget | Description | +|-------------------|---|---|---|-----------------------| +| [DMC Proprio](https://github.com/deepmind/dm_control) | State | Continuous | 500K | DeepMind Control Suite with low-dimensional inputs. | +| [DMC Vision](https://github.com/deepmind/dm_control) | Image | Continuous |1M| DeepMind Control Suite with high-dimensional images inputs. | +| [Atari 100k](https://github.com/openai/atari-py) | Image | Discrete |400K| 26 Atari games. | +| [Crafter](https://github.com/danijar/crafter) | Image | Discrete |1M| Survival environment to evaluates diverse agent abilities.| +| [Memory Maze](https://github.com/jurgisp/memory-maze) | Image |Discrete |100M| 3D mazes to evaluate RL agents' long-term memory.| ## Results -#### DMC Vision -![dmcvision](https://github.com/NM512/dreamerv3-torch/assets/70328564/b710d217-2428-4fa0-8471-55e15ec5aa43) - -#### Atari 100k -![atari100k](https://github.com/NM512/dreamerv3-torch/assets/70328564/0da6d899-d91d-44b4-a8c4-d5b37413aa11) - #### DMC Proprio ![dmcproprio](https://github.com/NM512/dreamerv3-torch/assets/70328564/7f6e47a5-3235-4bc4-bef9-15ff96782d5e) - +#### DMC Vision +![dmcvision](https://github.com/NM512/dreamerv3-torch/assets/70328564/b710d217-2428-4fa0-8471-55e15ec5aa43) +#### Atari 100k +![atari100k](https://github.com/NM512/dreamerv3-torch/assets/70328564/0da6d899-d91d-44b4-a8c4-d5b37413aa11) ## Acknowledgments This code is heavily inspired by the following works: