Nash bargaining solution
E2666
The Nash bargaining solution is a foundational concept in game theory that defines a fair and efficient outcome for two-party bargaining problems based on axioms of rationality and symmetry.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Nash bargaining solution canonical | 4 |
| The Bargaining Problem | 1 |
| article "The Bargaining Problem" | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T16348 — 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: Nash bargaining solution Context triple: [John Nash, notableIdea, Nash bargaining solution]
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A.
Non-cooperative Games
Non-cooperative Games is John Nash’s seminal 1950 paper that founded modern non-cooperative game theory and introduced the concept now known as Nash equilibrium.
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B.
Oskar Morgenstern
Oskar Morgenstern was an Austrian-American economist best known as the co-founder of game theory through his seminal work "Theory of Games and Economic Behavior" with John von Neumann.
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C.
John Nash
John Nash was an American mathematician renowned for his groundbreaking work in game theory, differential geometry, and partial differential equations, which profoundly influenced economics and the mathematical sciences.
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D.
Feynman–Kac formula
The Feynman–Kac formula is a fundamental result connecting solutions of certain partial differential equations with expectations over stochastic processes, forming a bridge between quantum mechanics, probability theory, and mathematical finance.
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E.
A Mathematical Theory of Communication
A Mathematical Theory of Communication is Claude Shannon’s landmark 1948 paper that founded information theory by rigorously defining concepts like information, entropy, and channel capacity.
- 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: Nash bargaining solution Target entity description: The Nash bargaining solution is a foundational concept in game theory that defines a fair and efficient outcome for two-party bargaining problems based on axioms of rationality and symmetry.
-
A.
Non-cooperative Games
Non-cooperative Games is John Nash’s seminal 1950 paper that founded modern non-cooperative game theory and introduced the concept now known as Nash equilibrium.
-
B.
Oskar Morgenstern
Oskar Morgenstern was an Austrian-American economist best known as the co-founder of game theory through his seminal work "Theory of Games and Economic Behavior" with John von Neumann.
-
C.
John Nash
John Nash was an American mathematician renowned for his groundbreaking work in game theory, differential geometry, and partial differential equations, which profoundly influenced economics and the mathematical sciences.
-
D.
Hamiltonian economic program
The Hamiltonian economic program was Alexander Hamilton’s comprehensive plan to strengthen the early United States’ financial system through federal assumption of state debts, creation of a national bank, and support for manufacturing and commerce.
-
E.
Feynman–Kac formula
The Feynman–Kac formula is a fundamental result connecting solutions of certain partial differential equations with expectations over stochastic processes, forming a bridge between quantum mechanics, probability theory, and mathematical finance.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
bargaining solution concept
ⓘ
cooperative game theory concept ⓘ solution concept in game theory ⓘ |
| appliesTo |
cooperative bargaining problem
ⓘ
two-person bargaining problem ⓘ |
| assumes |
transferable cardinal utilities up to positive affine transformations
ⓘ
von Neumann–Morgenstern utility functions ⓘ |
| author |
John Forbes Nash Jr.
ⓘ
linked to:
John Nash
|
| basedOn |
axiom of Pareto efficiency
ⓘ
axiom of independence of irrelevant alternatives ⓘ axiom of invariance to affine transformations of utility ⓘ axiom of symmetry ⓘ |
| category |
axiomatic game theory
ⓘ
bargaining theory ⓘ |
| characterizedBy |
Pareto efficiency
ⓘ
independence of irrelevant alternatives ⓘ scale invariance of utilities ⓘ symmetry between players ⓘ uniqueness under Nash’s axioms ⓘ |
| defines | unique outcome of a bargaining problem ⓘ |
| domainRestriction |
feasible set must be compact and convex
ⓘ
utilities at solution must weakly exceed disagreement utilities ⓘ |
| field |
economics
ⓘ
game theory ⓘ mathematics ⓘ |
| hasProperty |
Pareto optimal outcome
ⓘ
no player can be made better off without making the other worse off at the solution ⓘ voluntary participation by both players ⓘ |
| influenced |
axiomatic bargaining theory
ⓘ
contract theory ⓘ mechanism design ⓘ |
| introducedIn |
article "The Bargaining Problem"
ⓘ
linked to:
Nash bargaining solution
|
| maximizes | product of players’ utility gains over disagreement point ⓘ |
| namedAfter |
John Forbes Nash Jr.
ⓘ
linked to:
John Nash
|
| publicationYear | 1950 ⓘ |
| publishedIn | Econometrica ⓘ |
| relatedTo |
Kalai–Smorodinsky bargaining solution
ⓘ
Rubinstein bargaining model ⓘ cooperative game theory ⓘ |
| solutionForm | argmax of (u1 - d1)(u2 - d2) over feasible set ⓘ |
| usedIn |
bargaining in industrial organization
ⓘ
bargaining in international trade models ⓘ household bargaining models ⓘ labor negotiations modeling ⓘ |
| usesConcept |
disagreement point
ⓘ
feasible utility set ⓘ |
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: Nash bargaining solution Description of subject: The Nash bargaining solution is a foundational concept in game theory that defines a fair and efficient outcome for two-party bargaining problems based on axioms of rationality and symmetry.
Referenced by (6)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Nash bargaining solution
linked to: Nash bargaining solution