scholarly journals Rationalization and identification of binary games with correlated types

2017 ◽  
Vol 201 (2) ◽  
pp. 249-268 ◽  
Author(s):  
Nianqing Liu ◽  
Quang Vuong ◽  
Haiqing Xu
Keyword(s):  
2012 ◽  
Vol 166 (1) ◽  
pp. 92-105 ◽  
Author(s):  
Brendan Kline ◽  
Elie Tamer

2006 ◽  
Vol 28 (1) ◽  
pp. 125-143 ◽  
Author(s):  
Flavio M. Menezes ◽  
Rohan Pitchford
Keyword(s):  

1944 ◽  
Vol 28 (280) ◽  
pp. 96 ◽  
Author(s):  
R. S. Scorer ◽  
P. M. Grundy ◽  
C. A. B. Smith
Keyword(s):  

2016 ◽  
Vol 44 (1) ◽  
pp. 19-24 ◽  
Author(s):  
Guillaume Vigeral ◽  
Yannick Viossat
Keyword(s):  

2010 ◽  
Vol 10 (11&12) ◽  
pp. 911-924
Author(s):  
Salman Beigi

A two-player one-round binary game consists of two cooperative players who each replies by one bit to a message that he receives privately; they win the game if both questions and answers satisfy some predetermined property. A game is called entangled if the players are allowed to share a priori entanglement. It is well-known that the maximum winning probability (value) of entangled XOR-games (binary games in which the predetermined property depends only on the XOR of the two output bits) can be computed by a semidefinite program. In this paper we extend this result in the following sense; if a binary game is uniform, meaning that in an optimal strategy the marginal distributions of the output of each player are uniform, then its entangled value can be efficiently computed by a semidefinite program. We also introduce a lower bound on the entangled value of a general two-player one-round game; this bound depends on the size of the output set of each player and can be computed by a semidefinite program. In particular, we show that if the game is binary, $\omega_q$ is its entangled value, and $\omega_{sdp}$ is the optimum value of the corresponding semidefinite program, then $0.68\,\omega_{sdp} < \omega_q \leq \omega_{sdp}$.


2020 ◽  
Vol 16 (3) ◽  
pp. 211-220
Author(s):  
Leszek Szczecinski ◽  
Aymen Djebbi

AbstractThis work is concerned with the interpretation of the results produced by the well known Elo algorithm applied in various sport ratings. The interpretation consists in defining the probabilities of the game outcomes conditioned on the ratings of the players and should be based on the probabilistic rating-outcome model. Such a model is known in the binary games (win/loss), allowing us to interpret the rating results in terms of the win/loss probability. On the other hand, the model for the ternary outcomes (win/loss/draw) has not been yet shown even if the Elo algorithm has been used in ternary games from the very moment it was devised. Using the draw model proposed by Davidson in 1970, we derive a new Elo-Davidson algorithm, and show that the Elo algorithm is its particular instance. The parameters of the Elo-Davidson are then related to the frequency of draws which indicates that the Elo algorithm silently assumes games with 50% of draws. To remove this assumption, often unrealistic, the Elo-Davidson algorithm should be used as it improves the fit to the data. The behaviour of the algorithms is illustrated using the results from English Premier League.


1988 ◽  
Vol 16 (2) ◽  
pp. 189-201 ◽  
Author(s):  
Nicolas G. Andjiga ◽  
Joël Moulen

Entropy ◽  
2013 ◽  
Vol 15 (12) ◽  
pp. 4648-4667 ◽  
Author(s):  
Tomás Rodríguez Barraquer

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