Tianshou
E438349
Tianshou is a reinforcement learning library for PyTorch that provides modular, efficient tools and algorithms for training and evaluating RL agents.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Tianshou canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4425212 — 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: Tianshou Context triple: [PettingZoo, compatibleWith, Tianshou]
-
A.
Zheyuan
Zheyuan is a given name most notably borne by the Chinese general and politician Song Zheyuan.
-
B.
Zhiyuan
Zhiyuan was a late 19th-century protected cruiser of the Qing Dynasty’s Beiyang Fleet, best known for its role and sinking in the First Sino-Japanese War.
-
C.
Tsien
Tsien is a Chinese surname borne by several notable figures in science and engineering, including biophysicist Richard Tsien.
-
D.
Tiant
Tiant is a surname most notably associated with Cuban former Major League Baseball pitcher Luis Tiant, known for his distinctive delivery and success with the Boston Red Sox in the 1970s.
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E.
Enbo
Enbo is a given name most notably associated with Tang Enbo, a prominent Chinese Nationalist general during the Second Sino-Japanese War and Chinese Civil War.
- 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: Tianshou Target entity description: Tianshou is a reinforcement learning library for PyTorch that provides modular, efficient tools and algorithms for training and evaluating RL agents.
-
A.
Zheyuan
Zheyuan is a given name most notably borne by the Chinese general and politician Song Zheyuan.
-
B.
Zhiyuan
Zhiyuan was a late 19th-century protected cruiser of the Qing Dynasty’s Beiyang Fleet, best known for its role and sinking in the First Sino-Japanese War.
-
C.
Tsien
Tsien is a Chinese surname borne by several notable figures in science and engineering, including biophysicist Richard Tsien.
-
D.
Tiant
Tiant is a surname most notably associated with Cuban former Major League Baseball pitcher Luis Tiant, known for his distinctive delivery and success with the Boston Red Sox in the 1970s.
-
E.
Enbo
Enbo is a given name most notably associated with Tang Enbo, a prominent Chinese Nationalist general during the Second Sino-Japanese War and Chinese Civil War.
- F. None of above. chosen
Statements (50)
| Predicate | Object |
|---|---|
| instanceOf |
Python library
ⓘ
open-source software ⓘ reinforcement learning library ⓘ |
| deepLearningFramework | PyTorch NERFINISHED ⓘ |
| designGoal |
efficiency
ⓘ
modularity ⓘ reproducibility ⓘ |
| domain | reinforcement learning ⓘ |
| focusesOn |
practical RL applications
ⓘ
research in reinforcement learning ⓘ |
| hasFeature |
checkpointing utilities
ⓘ
collector abstraction ⓘ customizable components ⓘ evaluation utilities ⓘ high efficiency ⓘ logging integration ⓘ modular design ⓘ multi-agent reinforcement learning support ⓘ off-policy algorithms ⓘ on-policy algorithms ⓘ policy abstraction ⓘ replay buffer abstractions ⓘ training utilities ⓘ vectorized environment support ⓘ |
| license | MIT License ⓘ |
| programmingLanguage | Python ⓘ |
| provides |
evaluation pipelines for RL agents
ⓘ
example implementations of RL algorithms ⓘ training pipelines for RL agents ⓘ |
| repositoryPlatform | GitHub NERFINISHED ⓘ |
| supportsAlgorithm |
A2C
NERFINISHED
ⓘ
A3C NERFINISHED ⓘ C51 NERFINISHED ⓘ DDPG NERFINISHED ⓘ DQN NERFINISHED ⓘ Double DQN NERFINISHED ⓘ Dueling DQN NERFINISHED ⓘ PPO NERFINISHED ⓘ QR-DQN NERFINISHED ⓘ REINFORCE NERFINISHED ⓘ Rainbow DQN NERFINISHED ⓘ SAC NERFINISHED ⓘ TD3 NERFINISHED ⓘ TRPO NERFINISHED ⓘ |
| supportsEnvironment |
Atari environments
ⓘ
Gymnasium ⓘ Mujoco-like continuous control tasks ⓘ OpenAI Gym NERFINISHED ⓘ |
| supportsFramework | PyTorch NERFINISHED ⓘ |
| writtenIn | Python NERFINISHED ⓘ |
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: Tianshou Description of subject: Tianshou is a reinforcement learning library for PyTorch that provides modular, efficient tools and algorithms for training and evaluating RL agents.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.