OpenAI Baselines
E17813
OpenAI Baselines is a collection of high-quality reference implementations of reinforcement learning algorithms released by OpenAI for research and benchmarking.
All labels observed (2)
| Label | Occurrences |
|---|---|
| OpenAI Baselines canonical | 7 |
| Stable Baselines | 1 |
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
reinforcement learning toolkit
ⓘ
software library ⓘ |
| category | open-source software ⓘ |
| compatibleWith | OpenAI Gym ⓘ |
| dependsOn | TensorFlow ⓘ |
| developer | OpenAI ⓘ |
| feature |
common interfaces across algorithms
ⓘ
example training scripts ⓘ logging utilities ⓘ support for multiple environments ⓘ tested implementations ⓘ |
| genre |
machine learning software
ⓘ
reinforcement learning ⓘ |
| goal |
facilitate reproducible reinforcement learning research
ⓘ
provide high-quality reference implementations of RL algorithms ⓘ |
| implementsAlgorithm |
A2C
ⓘ
A3C ⓘ ACKTR ⓘ DDPG ⓘ Atari deep Q-network ⓘ
surface form:
DQN
DDPG ⓘ
surface form:
Deep Deterministic Policy Gradient
Atari deep Q-network ⓘ
surface form:
Deep Q-Network
Double DQN ⓘ Dueling DQN ⓘ GAIL ⓘ Her ⓘ
surface form:
HER
Hindsight Experience Replay ⓘ PPO ⓘ PPO2 ⓘ Prioritized Experience Replay DQN ⓘ TRPO ⓘ |
| inspired | Stable Baselines ⓘ |
| license | MIT License ⓘ |
| maintainer |
OpenAI
ⓘ
surface form:
OpenAI (historical)
|
| programmingLanguage | Python ⓘ |
| provides | reference implementations of reinforcement learning algorithms ⓘ |
| relatedTo | Stable Baselines ⓘ |
| repositoryPlatform | GitHub ⓘ |
| status | open source ⓘ |
| supports |
actor-critic methods
ⓘ
policy gradient methods ⓘ value-based methods ⓘ |
| targetAudience |
benchmark authors
ⓘ
machine learning researchers ⓘ reinforcement learning practitioners ⓘ |
| useCase |
algorithm comparison
ⓘ
benchmarking ⓘ research ⓘ |
| writtenIn | Python ⓘ |
Referenced by (8)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Stable Baselines