Richard S. Sutton
E753566
Richard S. Sutton is a pioneering computer scientist best known for his foundational contributions to reinforcement learning, including co-authoring the influential textbook "Reinforcement Learning: An Introduction."
All labels observed (3)
| Label | Occurrences |
|---|---|
| Richard S. Sutton canonical | 5 |
| Richard L. Sutton | 1 |
| Richard Sutton | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8732347 — 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: Richard S. Sutton Context triple: [Satinder Singh, coAuthor, Richard S. Sutton]
-
A.
Richard Sutton
Richard Sutton was a prominent early 16th-century English lawyer and benefactor best known for co-founding Brasenose College at the University of Oxford.
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B.
Stuart Russell
Stuart Russell is a leading artificial intelligence researcher and co-author of the seminal textbook "Artificial Intelligence: A Modern Approach," known for his influential work on AI theory, ethics, and safety.
-
C.
David Silver
David Silver is a leading artificial intelligence researcher best known for his work at DeepMind on reinforcement learning and the development of the AlphaGo system.
-
D.
David Silver
David Silver is a central character on the teen drama series "Beverly Hills, 90210," known for his evolution from an awkward outsider to a popular DJ and radio host.
-
E.
Andrew B. Moore
Andrew B. Moore was an American politician who served as governor of Alabama in the years leading up to and during the early part of the 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: Richard S. Sutton Target entity description: Richard S. Sutton is a pioneering computer scientist best known for his foundational contributions to reinforcement learning, including co-authoring the influential textbook "Reinforcement Learning: An Introduction."
-
A.
Richard Sutton
Richard Sutton was a prominent early 16th-century English lawyer and benefactor best known for co-founding Brasenose College at the University of Oxford.
-
B.
Stuart Russell
Stuart Russell is a leading artificial intelligence researcher and co-author of the seminal textbook "Artificial Intelligence: A Modern Approach," known for his influential work on AI theory, ethics, and safety.
-
C.
David Silver
David Silver is a leading artificial intelligence researcher best known for his work at DeepMind on reinforcement learning and the development of the AlphaGo system.
-
D.
David Silver
David Silver is a central character on the teen drama series "Beverly Hills, 90210," known for his evolution from an awkward outsider to a popular DJ and radio host.
-
E.
Andrew B. Moore
Andrew B. Moore was an American politician who served as governor of Alabama in the years leading up to and during the early part of the Civil War.
- F. None of above. chosen
Statements (45)
| Predicate | Object |
|---|---|
| instanceOf |
computer scientist
ⓘ
researcher ⓘ |
| affiliation |
Alberta Machine Intelligence Institute
ⓘ
DeepMind ⓘ |
| almaMater | University of Massachusetts Amherst ⓘ |
| citizenship |
Canada
ⓘ
United States ⓘ
linked to:
United States of America
|
| coAuthorOf | "Reinforcement Learning: An Introduction" ⓘ |
| coAuthorWith | Andrew G. Barto ⓘ |
| employer | University of Alberta ⓘ |
| fieldOfStudy | computer science ⓘ |
| fieldOfWork |
artificial intelligence
ⓘ
machine learning ⓘ reinforcement learning ⓘ |
| hasAcademicAdvisor | Andrew G. Barto ⓘ |
| hasContribution |
formalization of temporal-difference methods
ⓘ
integration of learning, planning, and acting in RL ⓘ popularization of reinforcement learning through textbooks and tutorials ⓘ theoretical foundations of reinforcement learning ⓘ |
| hasRole | pioneer of reinforcement learning ⓘ |
| influenced |
applications of reinforcement learning in games
ⓘ
applications of reinforcement learning in robotics ⓘ development of modern reinforcement learning ⓘ |
| knownFor |
actor-critic methods
ⓘ
foundational contributions to reinforcement learning ⓘ on-policy and off-policy learning methods ⓘ options framework for temporally extended actions ⓘ policy gradient methods ⓘ temporal-difference learning ⓘ the Dyna architecture ⓘ the book "Reinforcement Learning: An Introduction" ⓘ
linked to:
"Reinforcement Learning: An Introduction"
|
| language | English ⓘ |
| nationality |
American
ⓘ
Canadian ⓘ |
| notableWork |
Dyna reinforcement learning architecture
ⓘ
Q-learning related research ⓘ TD(λ) ⓘ
linked to:
TD(lambda)
actor-critic architectures ⓘ options framework in hierarchical reinforcement learning ⓘ policy gradient theorem ⓘ temporal-difference learning algorithms ⓘ |
| position |
professor
ⓘ
research scientist ⓘ |
| workInstitution |
DeepMind Alberta
ⓘ
linked to:
DeepMind
University of Alberta ⓘ |
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: Richard S. Sutton Description of subject: Richard S. Sutton is a pioneering computer scientist best known for his foundational contributions to reinforcement learning, including co-authoring the influential textbook "Reinforcement Learning: An Introduction."
Referenced by (7)
Full triples — surface form annotated when it differs from this entity's canonical label.