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 |
How this entity was disambiguated
This entity first appeared as the object of triple T146323 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OpenAI Baselines Context triple: [OpenAI, developed, OpenAI Baselines]
-
A.
OpenAI Gym
OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms through a standardized collection of environments and interfaces.
-
B.
DeepMind
DeepMind is a leading artificial intelligence research company renowned for breakthroughs such as AlphaGo and deep reinforcement learning, operating as a subsidiary of Google.
-
C.
OpenAI
OpenAI is an artificial intelligence research organization best known for developing advanced AI models such as ChatGPT and GPT series.
-
D.
Technical Committee on Robot Learning
The Technical Committee on Robot Learning is a specialized IEEE Robotics and Automation Society group that advances research and collaboration at the intersection of machine learning and robotics.
-
E.
Google Brain
Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: OpenAI Baselines Target entity description: OpenAI Baselines is a collection of high-quality reference implementations of reinforcement learning algorithms released by OpenAI for research and benchmarking.
-
A.
OpenAI Gym
OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms through a standardized collection of environments and interfaces.
-
B.
DeepMind
DeepMind is a leading artificial intelligence research company renowned for breakthroughs such as AlphaGo and deep reinforcement learning, operating as a subsidiary of Google.
-
C.
OpenAI
OpenAI is an artificial intelligence research organization best known for developing advanced AI models such as ChatGPT and GPT series.
-
D.
Technical Committee on Robot Learning
The Technical Committee on Robot Learning is a specialized IEEE Robotics and Automation Society group that advances research and collaboration at the intersection of machine learning and robotics.
-
E.
Google Brain
Google Brain is a deep learning research team at Google that pioneered many advances in neural networks and artificial intelligence.
- F. None of above. chosen
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 ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: OpenAI Baselines Description of subject: OpenAI Baselines is a collection of high-quality reference implementations of reinforcement learning algorithms released by OpenAI for research and benchmarking.
Referenced by (8)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Stable Baselines