OpenAI Gym
E17413
OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms through a standardized collection of environments and interfaces.
All labels observed (5)
| Label | Occurrences |
|---|---|
| OpenAI Gym canonical | 10 |
| Atari environments | 1 |
| OpenAI Gym benchmark tasks | 1 |
| OpenAI Gym environments | 1 |
| OpenAI Gym project | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T146322 — 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 Gym Context triple: [OpenAI, developed, OpenAI Gym]
-
A.
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.
-
B.
OpenAI
OpenAI is an artificial intelligence research organization best known for developing advanced AI models such as ChatGPT and GPT series.
-
C.
Element AI
Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
-
D.
DARPA Robotics Challenge
The DARPA Robotics Challenge was a high-profile international competition that pushed the development of advanced humanoid robots capable of performing complex disaster-response tasks in environments designed for humans.
-
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 Gym Target entity description: OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms through a standardized collection of environments and interfaces.
-
A.
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.
-
B.
OpenAI
OpenAI is an artificial intelligence research organization best known for developing advanced AI models such as ChatGPT and GPT series.
-
C.
Element AI
Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
-
D.
DARPA Robotics Challenge
The DARPA Robotics Challenge was a high-profile international competition that pushed the development of advanced humanoid robots capable of performing complex disaster-response tasks in environments designed for humans.
-
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 (48)
| Predicate | Object |
|---|---|
| instanceOf |
open-source software
ⓘ
reinforcement learning library ⓘ software toolkit ⓘ |
| category |
OpenAI projects
ⓘ
Python libraries ⓘ reinforcement learning software ⓘ |
| compatibleWith |
JAX
ⓘ
PyTorch ⓘ TensorFlow ⓘ |
| defines | Env API ⓘ |
| developer | OpenAI ⓘ |
| feature |
benchmark tasks
ⓘ
standardized collection of environments ⓘ standardized interfaces ⓘ |
| genre |
machine learning
ⓘ
reinforcement learning ⓘ |
| hasComponent |
OpenAI Gym
self-linksurface differs
ⓘ
surface form:
Atari environments
Box2D environments ⓘ MuJoCo environments ⓘ algorithmic environments ⓘ classic control environments ⓘ toy text environments ⓘ |
| hasSuccessor | Gymnasium ⓘ |
| influenced |
Gymnasium
ⓘ
PettingZoo ⓘ RLlib ⓘ OpenAI Baselines ⓘ
surface form:
Stable Baselines
|
| influencedBy | Arcade Learning Environment ⓘ |
| initialReleaseDate | 2016 ⓘ |
| interface |
render function
ⓘ
reset function ⓘ seed function ⓘ step function ⓘ |
| license | MIT License ⓘ |
| programmingLanguage | Python ⓘ |
| provides | standard RL benchmarking protocol ⓘ |
| purpose |
compare reinforcement learning algorithms
ⓘ
develop reinforcement learning algorithms ⓘ |
| repository | https://github.com/openai/gym ⓘ |
| supports |
OpenAI Baselines
ⓘ
continuous action spaces ⓘ discrete action spaces ⓘ observation spaces ⓘ vectorized environments ⓘ |
| usedFor |
benchmarking RL algorithms
ⓘ
education in reinforcement learning ⓘ research in reinforcement learning ⓘ |
| website | https://gym.openai.com ⓘ |
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 Gym Description of subject: OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms through a standardized collection of environments and interfaces.
Referenced by (14)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
Atari environments
this entity surface form:
OpenAI Gym project
this entity surface form:
OpenAI Gym environments
this entity surface form:
OpenAI Gym benchmark tasks