ALE
E438355
ALE is a widely used research platform that provides a common interface to hundreds of Atari 2600 games for developing and evaluating artificial intelligence and reinforcement learning algorithms.
All labels observed (1)
| Label | Occurrences |
|---|---|
| ALE canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4425296 — 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: ALE Context triple: [Arcade Learning Environment, shortName, ALE]
-
A.
AL
AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
-
B.
AL
AL is the official postal abbreviation for the Brazilian state of Alagoas, located in the country's Northeast region.
-
C.
AL
AL is the two-letter ISO 3166 country code representing the Republic of Albania.
-
D.
Ale
Ale is a common short form of the Italian given name Alessandro, often used as a casual or affectionate nickname.
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E.
ARE
ARE is a professional licensure examination for architects in the United States that assesses candidates’ knowledge and skills required for independent practice.
- 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: ALE Target entity description: ALE is a widely used research platform that provides a common interface to hundreds of Atari 2600 games for developing and evaluating artificial intelligence and reinforcement learning algorithms.
-
A.
AL
AL is the common abbreviation for the American League, one of the two major professional baseball leagues that make up Major League Baseball in the United States and Canada.
-
B.
AL
AL is the official postal abbreviation for the Brazilian state of Alagoas, located in the country's Northeast region.
-
C.
AL
AL is the two-letter ISO 3166 country code representing the Republic of Albania.
-
D.
Ale
Ale is a common short form of the Italian given name Alessandro, often used as a casual or affectionate nickname.
-
E.
ARE
ARE is a professional licensure examination for architects in the United States that assesses candidates’ knowledge and skills required for independent practice.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
reinforcement learning benchmark suite
ⓘ
research platform ⓘ software framework ⓘ |
| acronymFor | Arcade Learning Environment ⓘ |
| benchmarkProperty |
fixed action spaces per game
ⓘ
high-dimensional visual input ⓘ long-term credit assignment challenges ⓘ shared observation format across games ⓘ sparse and delayed rewards in many games ⓘ |
| domain |
artificial intelligence research
ⓘ
reinforcement learning research ⓘ |
| enables | comparison of RL algorithms on common tasks ⓘ |
| environmentType | discrete-time Markov decision process ⓘ |
| evaluationMetric |
average return over episodes
ⓘ
game score ⓘ |
| fullName | Arcade Learning Environment ⓘ |
| gamePlatform | Atari 2600 ⓘ |
| hasInfluenced |
development of deep Q-networks
ⓘ
standard RL benchmarking practices ⓘ |
| inputType | raw game screen pixels ⓘ |
| license | open source ⓘ |
| operatingSystem | cross-platform ⓘ |
| outputType | discrete game actions ⓘ |
| platformType | game-based AI benchmark ⓘ |
| provides |
common benchmark tasks
ⓘ
reproducible experimental setup ⓘ standardized environment API ⓘ |
| providesInterfaceTo | Atari 2600 games ⓘ |
| researchArea |
control under uncertainty
ⓘ
sequential decision making ⓘ |
| supports | hundreds of Atari 2600 games ⓘ |
| supportsFeature |
deterministic game modes
ⓘ
frame skipping ⓘ game state inspection ⓘ game state saving and loading ⓘ reward signal access ⓘ stochastic game modes ⓘ |
| supportsTask |
deep reinforcement learning
ⓘ
imitation learning experiments ⓘ policy-based reinforcement learning ⓘ value-based reinforcement learning ⓘ |
| timeScale | real-time game simulation ⓘ |
| usedBy |
machine learning researchers
ⓘ
reinforcement learning practitioners ⓘ |
| usedFor |
benchmarking AI agents
ⓘ
developing reinforcement learning algorithms ⓘ evaluating reinforcement learning algorithms ⓘ |
| usedIn |
academic research papers
ⓘ
algorithm comparison studies ⓘ |
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: ALE Description of subject: ALE is a widely used research platform that provides a common interface to hundreds of Atari 2600 games for developing and evaluating artificial intelligence and reinforcement learning algorithms.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.