scholarly journals Computing the Shapley value in allocation problems: approximations and bounds, with an application to the Italian VQR research assessment program

2018 ◽  
Vol 30 (4) ◽  
pp. 505-524 ◽  
Author(s):  
Francesco Lupia ◽  
Angelo Mendicelli ◽  
Andrea Ribichini ◽  
Francesco Scarcello ◽  
Marco Schaerf
Keyword(s):  
Shapley Value ◽  
Research Assessment ◽  
Assessment Program ◽  
The Shapley Value ◽  
Allocation Problems

On the Shapley value and its application to the Italian VQR research assessment exercise

2019 ◽  
Vol 13 (1) ◽  
pp. 87-104 ◽  
Author(s):  
Camil Demetrescu ◽  
Francesco Lupia ◽  
Angelo Mendicelli ◽  
Andrea Ribichini ◽  
Francesco Scarcello ◽  
...  
Keyword(s):  
Shapley Value ◽  
Research Assessment ◽  
Research Assessment Exercise ◽  
The Shapley Value

scholarly journals UNCERTAINTY OF THE SHAPLEY VALUE

2005 ◽  
Vol 07 (04) ◽  
pp. 517-529 ◽  
Author(s):  
VLADISLAV KARGIN
Keyword(s):  
Shapley Value ◽  
Cost Allocation ◽  
Competitive Equilibrium ◽  
Allocation Problem ◽  
Majority Voting ◽  
Market Games ◽  
Strategic Risk ◽  
The Shapley Value ◽  
Allocation Problems

This paper defines a measure of bargaining uncertainty that quantifies Roth's concept of strategic risk. It shows how this measure can be used for checking reliability of the Shapley value in cost allocation problems and in the theory of competitive equilibrium. Salient properties of the new measure are investigated and illustrated by examples of majority voting and market games and by a cost allocation problem from epidemiology.

Query Games in Databases

2021 ◽  
Vol 50 (1) ◽  
pp. 78-85
Author(s):  
Ester Livshits ◽  
Leopoldo Bertossi ◽  
Benny Kimelfeld ◽  
Moshe Sebag
Keyword(s):  
Game Theory ◽  
Cooperative Game ◽  
Shapley Value ◽  
Cooperative Game Theory ◽  
The Shapley Value ◽  
Computational Aspects ◽  
Aggregate Query ◽  
Boolean Query

Database tuples can be seen as players in the game of jointly realizing the answer to a query. Some tuples may contribute more than others to the outcome, which can be a binary value in the case of a Boolean query, a number for a numerical aggregate query, and so on. To quantify the contributions of tuples, we use the Shapley value that was introduced in cooperative game theory and has found applications in a plethora of domains. Specifically, the Shapley value of an individual tuple quantifies its contribution to the query. We investigate the applicability of the Shapley value in this setting, as well as the computational aspects of its calculation in terms of complexity, algorithms, and approximation.

scholarly journals A new basis and the Shapley value

2016 ◽  
Vol 80 ◽  
pp. 21-24 ◽  
Author(s):  
Koji Yokote ◽  
Yukihiko Funaki ◽  
Yoshio Kamijo
Keyword(s):  
Shapley Value ◽  
The Shapley Value

COPING WITH UNCERTAINTY IN n-PERSON GAMES

2000 ◽  
Vol 08 (05) ◽  
pp. 503-523 ◽  
Author(s):  
SILVIU GUIASU
Keyword(s):  
Characteristic Function ◽  
Security Council ◽  
Shapley Value ◽  
Statistical Equilibrium ◽  
Individual Rationality ◽  
Von Neumann ◽  
Minimum Deviation ◽  
The Shapley Value ◽  
Un Security Council ◽  
Person Game

A solution of n-person games is proposed, based on the minimum deviation from statistical equilibrium subject to the constraints imposed by the group rationality and individual rationality. The new solution is compared with the Shapley value and von Neumann-Morgenstern's core of the game in the context of the 15-person game of passing and defeating resolutions in the UN Security Council involving five permanent members and ten nonpermanent members. A coalition classification, based on the minimum ramification cost induced by the characteristic function of the game, is also presented.

Shapley Ranking of Wines

2012 ◽  
Vol 7 (2) ◽  
pp. 169-180 ◽  
Author(s):  
Victor Ginsburgh ◽  
Israël Zang
Keyword(s):  
Game Theory ◽  
Unique Solution ◽  
Cooperative Game ◽  
Shapley Value ◽  
Rank Order ◽  
Jel Classification ◽  
Ranking Method ◽  
The Shapley Value ◽  
Shapley Values

AbstractWe suggest a new game-theory-based ranking method for wines, in which the Shapley Value of each wine is computed, and wines are ranked according to their Shapley Values. Judges should find it simpler to use, since they are not required to rank order or grade all the wines, but merely to choose the group of those that they find meritorious. Our ranking method is based on the set of reasonable axioms that determine the Shapley Value as the unique solution of an underlying cooperative game. Unlike in the general case, where computing the Shapley Value could be complex, here the Shapley Value and hence the final ranking, are straightforward to compute. (JEL Classification: C71, D71, D78)

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