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---
language:
- en
license: apache-2.0
size_categories:
- 10M<n<100M
task_categories:
- reinforcement-learning
pretty_name: Procgen Benchmark Dataset
dataset_info:
- config_name: bigfish
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
num_bytes: 28937250000
num_examples: 1000000
download_size: 63430147458
dataset_size: 289372500000
- config_name: bossfight
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
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num_examples: 1000000
download_size: 106055802563
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- config_name: caveflyer
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
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num_examples: 9000000
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- config_name: chaser
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
num_bytes: 28937250000
num_examples: 1000000
download_size: 42555126877
dataset_size: 289372500000
- config_name: climber
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
num_bytes: 28937250000
num_examples: 1000000
download_size: 42586772888
dataset_size: 289372500000
- config_name: coinrun
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
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download_size: 51408569531
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- config_name: dodgeball
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
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num_examples: 9000000
- name: test
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download_size: 69558620534
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- config_name: fruitbot
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: test
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num_examples: 1000000
- name: train
num_bytes: 260435250000
num_examples: 9000000
download_size: 263161438347
dataset_size: 289372500000
- config_name: heist
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
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num_examples: 9000000
- name: test
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num_examples: 1000000
download_size: 49646772230
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- config_name: jumper
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
num_bytes: 28937250000
num_examples: 1000000
download_size: 67531643053
dataset_size: 289372500000
- config_name: leaper
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
num_bytes: 28937250000
num_examples: 1000000
download_size: 44464909989
dataset_size: 289372500000
- config_name: maze
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
num_bytes: 28937250000
num_examples: 1000000
download_size: 50930919120
dataset_size: 289372500000
- config_name: miner
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
num_bytes: 28937250000
num_examples: 1000000
download_size: 38184188600
dataset_size: 289372500000
- config_name: ninja
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
num_bytes: 28937250000
num_examples: 1000000
download_size: 66644794325
dataset_size: 289372500000
- config_name: plunder
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
num_bytes: 28937250000
num_examples: 1000000
download_size: 68795928729
dataset_size: 289372500000
- config_name: starpilot
features:
- name: observation
dtype:
array3_d:
shape:
- 64
- 64
- 3
dtype: uint8
- name: action
dtype: uint8
- name: reward
dtype: float32
- name: done
dtype: bool
- name: truncated
dtype: bool
splits:
- name: train
num_bytes: 260435250000
num_examples: 9000000
- name: test
num_bytes: 28937250000
num_examples: 1000000
download_size: 170031712117
dataset_size: 289372500000
configs:
- config_name: bigfish
data_files:
- split: train
path: bigfish/train-*
- split: test
path: bigfish/test-*
- config_name: bossfight
data_files:
- split: train
path: bossfight/train-*
- split: test
path: bossfight/test-*
- config_name: caveflyer
data_files:
- split: train
path: caveflyer/train-*
- split: test
path: caveflyer/test-*
- config_name: chaser
data_files:
- split: train
path: chaser/train-*
- split: test
path: chaser/test-*
- config_name: climber
data_files:
- split: train
path: climber/train-*
- split: test
path: climber/test-*
- config_name: coinrun
data_files:
- split: train
path: coinrun/train-*
- split: test
path: coinrun/test-*
- config_name: dodgeball
data_files:
- split: train
path: dodgeball/train-*
- split: test
path: dodgeball/test-*
- config_name: fruitbot
data_files:
- split: train
path: fruitbot/train-*
- split: test
path: fruitbot/test-*
- config_name: heist
data_files:
- split: train
path: heist/train-*
- split: test
path: heist/test-*
- config_name: jumper
data_files:
- split: train
path: jumper/train-*
- split: test
path: jumper/test-*
- config_name: leaper
data_files:
- split: train
path: leaper/train-*
- split: test
path: leaper/test-*
- config_name: maze
data_files:
- split: train
path: maze/train-*
- split: test
path: maze/test-*
- config_name: miner
data_files:
- split: train
path: miner/train-*
- split: test
path: miner/test-*
- config_name: ninja
data_files:
- split: train
path: ninja/train-*
- split: test
path: ninja/test-*
- config_name: plunder
data_files:
- split: train
path: plunder/train-*
- split: test
path: plunder/test-*
- config_name: starpilot
data_files:
- split: train
path: starpilot/train-*
- split: test
path: starpilot/test-*
tags:
- procgen
- bigfish
- benchmark
- openai
- bossfight
- caveflyer
- chaser
- climber
- dodgeball
- fruitbot
- heist
- jumper
- leaper
- maze
- miner
- ninja
- plunder
- starpilot
---
# Procgen Benchmark
This dataset contains expert trajectories generated by a [PPO](https://arxiv.org/abs/1707.06347) reinforcement learning agent trained on each of the 16 procedurally-generated gym environments from the [Procgen Benchmark](https://openai.com/index/procgen-benchmark/). The environments were created on `distribution_mode=easy` and with unlimited levels.
Disclaimer: This is not an official repository from OpenAI.
## Dataset Usage
Regular usage (for environment bigfish):
```python
from datasets import load_dataset
train_dataset = load_dataset("EpicPinkPenguin/procgen", name="bigfish", split="train")
test_dataset = load_dataset("EpicPinkPenguin/procgen", name="bigfish", split="test")
```
Usage with PyTorch (for environment bossfight):
```python
from datasets import load_dataset
train_dataset = load_dataset("EpicPinkPenguin/procgen", name="bossfight", split="train").with_format("torch")
test_dataset = load_dataset("EpicPinkPenguin/procgen", name="bossfight", split="test").with_format("torch")
```
## Agent Performance
The PPO RL agent was trained for 50M steps on each environment and obtained the following final performance metrics.
| Environment | Steps (Train) | Steps (Test) | Return | Observation |
|:------------|:----------------|:---------------|:-------|:------------|
| bigfish | 9,000,000 | 1,000,000 | 29.38 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/lHQXBqLdoWicXlt68I9QX.mp4"></video> |
| bossfight | 9,000,000 | 1,000,000 | 10.86 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/LPoafGi4YBWqqkuFlEN_l.mp4"></video> |
| caveflyer | 9,000,000 | 1,000,000 | 09.58 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/XVqRwu_9yfX4ECQc4At4G.mp4"></video> |
| chaser | 9,000,000 | 1,000,000 | 11.52 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/FIKVv48SThqiC1Z2PYQ7U.mp4"></video> |
| climber | 9,000,000 | 1,000,000 | 10.66 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/XJQlA7IyF9_gwUiw-FkND.mp4"></video> |
| coinrun | 9,000,000 | 1,000,000 | 09.84 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/Ucv3HZttewMRQzTL8r_Tw.mp4"></video> |
| dodgeball | 9,000,000 | 1,000,000 | 16.73 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/5HetbKuXBpO-v1jcVyLTU.mp4"></video> |
| fruitbot | 9,000,000 | 1,000,000 | 21.39 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/zKCyxXvauXjUac-5kEAWz.mp4"></video> |
| heist | 9,000,000 | 1,000,000 | 09.95 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/AdZ6XNmUN5_00BKd9BN8R.mp4"></video> |
| jumper | 9,000,000 | 1,000,000 | 08.76 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/s5k31gWK2Vc6Lp6QVzQXA.mp4"></video> |
| leaper | 9,000,000 | 1,000,000 | 07.50 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/_hDMocxjmzutc0t5FfoTX.mp4"></video> |
| maze | 9,000,000 | 1,000,000 | 09.99 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/uhNdDPuNhZpxVns91Ba-9.mp4"></video> |
| miner | 9,000,000 | 1,000,000 | 12.66 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/ElpJ8l2WHJGrprZ3-giHU.mp4"></video> |
| ninja | 9,000,000 | 1,000,000 | 09.61 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/b9i-fb2Twh8XmBBNf2DRG.mp4"></video> |
| plunder | 9,000,000 | 1,000,000 | 25.68 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/JPeGNOVzrotuYUjfzZj40.mp4"></video> |
| starpilot | 9,000,000 | 1,000,000 | 57.25 | <video controls autoplay loop src="https://cdn-uploads.huggingface.co/production/uploads/633c1daf31c06121a58f2df9/wY9lZgkw5tor19hCWmm6A.mp4"></video> |
## Dataset Structure
### Data Instances
Each data instance represents a single step consisting of tuples of the form (observation, action, reward, done, truncated) = (o_t, a_t, r_{t+1}, done_{t+1}, trunc_{t+1}).
```json
{'action': 1,
'done': False,
'observation': [[[0, 166, 253],
[0, 174, 255],
[0, 170, 251],
[0, 191, 255],
[0, 191, 255],
[0, 221, 255],
[0, 243, 255],
[0, 248, 255],
[0, 243, 255],
[10, 239, 255],
[25, 255, 255],
[0, 241, 255],
[0, 235, 255],
[17, 240, 255],
[10, 243, 255],
[27, 253, 255],
[39, 255, 255],
[58, 255, 255],
[85, 255, 255],
[111, 255, 255],
[135, 255, 255],
[151, 255, 255],
[173, 255, 255],
...
[0, 0, 37],
[0, 0, 39]]],
'reward': 0.0,
'truncated': False}
```
### Data Fields
- `observation`: The current RGB observation from the environment.
- `action`: The action predicted by the agent for the current observation.
- `reward`: The received reward from stepping the environment with the current action.
- `done`: If the new observation is the start of a new episode. Obtained after stepping the environment with the current action.
- `truncated`: If the new observation is the start of a new episode due to truncation. Obtained after stepping the environment with the current action.
### Data Splits
The dataset is divided into a `train` (90%) and `test` (10%) split. Each environment-dataset has in sum 10M steps (data points).
## Dataset Creation
The dataset was created by training an RL agent with [PPO](https://arxiv.org/abs/1707.06347) for 25M steps in each environment. The trajectories where generated by sampling from the predicted action distribution at each step (not taking the argmax). The environments were created on `distribution_mode=easy` and with unlimited levels.
## Procgen Benchmark
The [Procgen Benchmark](https://openai.com/index/procgen-benchmark/), released by OpenAI, consists of 16 procedurally-generated environments designed to measure how quickly reinforcement learning (RL) agents learn generalizable skills. It emphasizes experimental convenience, high diversity within and across environments, and is ideal for evaluating both sample efficiency and generalization. The benchmark allows for distinct training and test sets in each environment, making it a standard research platform for the OpenAI RL team. It aims to address the need for more diverse RL benchmarks compared to complex environments like Dota and StarCraft.