Joel Veness
E774594
Joel Veness is a computer scientist and researcher known for his work in artificial intelligence and algorithmic information theory, including collaborations with Marcus Hutter.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Joel Veness canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T9062815 — 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: Joel Veness Context triple: [Marcus Hutter, coAuthorWith, Joel Veness]
-
A.
Noah Falstein
Noah Falstein is a veteran video game designer best known for his work at LucasArts on classic adventure titles such as Indiana Jones and the Fate of Atlantis.
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B.
Joel Reynolds
Joel Reynolds is a fictional protagonist whose story centers on his personal experiences and development within the narrative from which he is drawn.
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C.
Joel McAndrew
Joel McAndrew is a New York–based hedge fund manager best known as the husband of English model and actress Agyness Deyn.
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D.
Joel
Joel is a masculine given name of Hebrew origin meaning "Yahweh is God," commonly used in many English-speaking and other countries.
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E.
Joel
Joel is a prophetic book in the Old Testament that focuses on themes of divine judgment, repentance, and the coming "day of the Lord."
- 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: Joel Veness Target entity description: Joel Veness is a computer scientist and researcher known for his work in artificial intelligence and algorithmic information theory, including collaborations with Marcus Hutter.
-
A.
Noah Falstein
Noah Falstein is a veteran video game designer best known for his work at LucasArts on classic adventure titles such as Indiana Jones and the Fate of Atlantis.
-
B.
Joel Reynolds
Joel Reynolds is a fictional protagonist whose story centers on his personal experiences and development within the narrative from which he is drawn.
-
C.
Joel McAndrew
Joel McAndrew is a New York–based hedge fund manager best known as the husband of English model and actress Agyness Deyn.
-
D.
Joel
Joel is a prophetic book in the Old Testament that focuses on themes of divine judgment, repentance, and the coming "day of the Lord."
-
E.
Joel
Joel is a masculine given name of Hebrew origin meaning "Yahweh is God," commonly used in many English-speaking and other countries.
- F. None of above. chosen
Statements (42)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
researcher ⓘ |
| affiliation | DeepMind NERFINISHED ⓘ |
| coauthoredWith |
David Silver
NERFINISHED
ⓘ
Demis Hassabis NERFINISHED ⓘ Karen Simonyan NERFINISHED ⓘ Kee Siong Ng NERFINISHED ⓘ Koray Kavukcuoglu NERFINISHED ⓘ Marcus Hutter NERFINISHED ⓘ Michael Bowling NERFINISHED ⓘ Simon Schmitt NERFINISHED ⓘ Tom Schaul NERFINISHED ⓘ Wojciech Czarnecki NERFINISHED ⓘ |
| collaboratedWith | Marcus Hutter NERFINISHED ⓘ |
| countryOfCitizenship | Australia ⓘ |
| educatedAt | University of Alberta NERFINISHED ⓘ |
| employer | DeepMind NERFINISHED ⓘ |
| fieldOfWork |
algorithmic information theory
ⓘ
artificial intelligence ⓘ machine learning ⓘ reinforcement learning ⓘ |
| hasGivenTalkAt |
AI and RL seminars
ⓘ
NIPS workshops NERFINISHED ⓘ |
| knownFor |
applications of algorithmic information theory to AI
ⓘ
research on universal prediction and planning ⓘ work on Monte Carlo search methods ⓘ work on reinforcement learning agents ⓘ |
| language | English ⓘ |
| notableConcept | practical approximations to AIXI ⓘ |
| notableWork |
A Monte Carlo AIXI Approximation
NERFINISHED
ⓘ
Reinforcement Learning via AIXI Approximation NERFINISHED ⓘ |
| notableWorkArea | universal artificial intelligence ⓘ |
| publishedIn |
Advances in Neural Information Processing Systems
NERFINISHED
ⓘ
International Conference on Machine Learning NERFINISHED ⓘ Journal of Artificial Intelligence Research NERFINISHED ⓘ Proceedings of the AAAI Conference on Artificial Intelligence NERFINISHED ⓘ |
| researchInterest |
general reinforcement learning
ⓘ
planning under uncertainty ⓘ universal sequence prediction ⓘ |
| supervisedBy | Michael Bowling NERFINISHED ⓘ |
| worksOn |
game-playing AI agents
ⓘ
scalable reinforcement learning algorithms ⓘ |
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: Joel Veness Description of subject: Joel Veness is a computer scientist and researcher known for his work in artificial intelligence and algorithmic information theory, including collaborations with Marcus Hutter.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.