2017
DOI: 10.1007/s11128-017-1738-0
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Playing distributed two-party quantum games on quantum networks

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Cited by 11 publications
(3 citation statements)
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“…In other words, entanglement cannot enhance the cooperation if the profit distribution polices are not reasonable or fair. Our recent research [28] also indicates that entanglement can also be utilized to enhance the cooperation of distant players with the help of quantum networks. We come 030202-4 to realize that neither quantum entanglement nor quantum network can offer full cooperation without fair profit distribution policies.…”
Section: Discussionmentioning
confidence: 99%
“…In other words, entanglement cannot enhance the cooperation if the profit distribution polices are not reasonable or fair. Our recent research [28] also indicates that entanglement can also be utilized to enhance the cooperation of distant players with the help of quantum networks. We come 030202-4 to realize that neither quantum entanglement nor quantum network can offer full cooperation without fair profit distribution policies.…”
Section: Discussionmentioning
confidence: 99%
“…It has also been exemplified in Refs. [32][33][34] that quantum entanglement and fairness will promote full cooperation among distant peoples from various interest groups based on quantization of the extended classical 'cash in a hat' game. Full cooperation relies on not only the degree of quantum entanglement but also the degree of fairness.…”
Section: -2mentioning
confidence: 99%
“…Previous studies on quantum games generally focus on one of these two stages. For instance, the Eisert-Lewenstein-Wilkens quantum game scheme [9,[13][14][15][16] concentrates on the quantization of strategy negotiation process, where strategy operations are expanded from classical bit operators to unitary quantum gates, and the measurement basis for move decision is assumed to be constant. In contrast, players adjust the measurement basis in Marinatto's scheme [17][18][19][20][21] and Bayesian quantum games [22][23][24][25][26][27][28] to optimize their move decision policies.…”
Section: Introductionmentioning
confidence: 99%