Michael L. Littman
E753099
Michael L. Littman is an American computer scientist and professor known for his influential research in reinforcement learning, machine learning, and artificial intelligence.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Michael L. Littman canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8732350 — 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: Michael L. Littman Context triple: [Satinder Singh, coAuthor, Michael L. Littman]
-
A.
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.
-
B.
Wolfram Burgard
Wolfram Burgard is a German computer scientist and roboticist known for his influential work in probabilistic robotics, autonomous navigation, and artificial intelligence.
-
C.
Michael N. Marcus
Michael N. Marcus is a screenwriter best known for his work on the 1966 Western film "Duel at Diablo."
-
D.
Michael P. Kearns
Michael P. Kearns is an American politician from New York who has served in various local and state offices, including roles in the New York State Assembly and Erie County government.
-
E.
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.
- 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: Michael L. Littman Target entity description: Michael L. Littman is an American computer scientist and professor known for his influential research in reinforcement learning, machine learning, and artificial intelligence.
-
A.
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.
-
B.
Wolfram Burgard
Wolfram Burgard is a German computer scientist and roboticist known for his influential work in probabilistic robotics, autonomous navigation, and artificial intelligence.
-
C.
Michael N. Marcus
Michael N. Marcus is a screenwriter best known for his work on the 1966 Western film "Duel at Diablo."
-
D.
Michael P. Kearns
Michael P. Kearns is an American politician from New York who has served in various local and state offices, including roles in the New York State Assembly and Erie County government.
-
E.
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.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
artificial intelligence researcher
ⓘ
person ⓘ university professor ⓘ |
| academicDegree | PhD in computer science ⓘ |
| citizenship | American ⓘ |
| countryOfCitizenship | United States of America ⓘ |
| educatedAt | Brown University ⓘ |
| employer |
Brown University
NERFINISHED
ⓘ
Duke University NERFINISHED ⓘ Rutgers University NERFINISHED ⓘ |
| fieldOfWork |
artificial intelligence
ⓘ
computational game theory ⓘ computer science ⓘ educational technology ⓘ machine learning ⓘ multi-agent systems ⓘ reinforcement learning ⓘ |
| gender | male ⓘ |
| hasAcademicAdvisor | Leslie P. Kaelbling NERFINISHED ⓘ |
| hasResearchInterest |
AI education
ⓘ
human-centered AI ⓘ planning under uncertainty ⓘ sequential decision making ⓘ |
| hasRole |
AAAI Fellow
NERFINISHED
ⓘ
ACM Fellow NERFINISHED ⓘ |
| hasStudent |
Amy Greenwald
NERFINISHED
ⓘ
Doina Precup NERFINISHED ⓘ Emma Brunskill NERFINISHED ⓘ Michael Bowling NERFINISHED ⓘ Satinder Singh NERFINISHED ⓘ |
| knownFor |
research in artificial intelligence
ⓘ
research in machine learning ⓘ research in reinforcement learning ⓘ work on Markov decision processes ⓘ work on game-theoretic approaches to reinforcement learning ⓘ work on multi-agent reinforcement learning ⓘ |
| languageSpoken | English ⓘ |
| memberOf |
Association for Computing Machinery
NERFINISHED
ⓘ
Association for the Advancement of Artificial Intelligence NERFINISHED ⓘ |
| notableWork |
research on game-theoretic planning
ⓘ
research on multi-agent reinforcement learning ⓘ research on partially observable Markov decision processes ⓘ research on reinforcement learning algorithms ⓘ |
| occupation | professor of computer science ⓘ |
| positionHeld |
faculty member at Duke University
ⓘ
professor at Brown University ⓘ professor at Rutgers University ⓘ |
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: Michael L. Littman Description of subject: Michael L. Littman is an American computer scientist and professor known for his influential research in reinforcement learning, machine learning, and artificial intelligence.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.