scholarly journals Entangled N-photon states for fair and optimal social decision making

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nicolas Chauvet ◽  
Guillaume Bachelier ◽  
Serge Huant ◽  
Hayato Saigo ◽  
Hirokazu Hori ◽  
...  

AbstractSituations involving competition for resources among entities can be modeled by the competitive multi-armed bandit (CMAB) problem, which relates to social issues such as maximizing the total outcome and achieving the fairest resource repartition among individuals. In these respects, the intrinsic randomness and global properties of quantum states provide ideal tools for obtaining optimal solutions to this problem. Based on the previous study of the CMAB problem in the two-arm, two-player case, this paper presents the theoretical principles necessary to find polarization-entangled N-photon states that can optimize the total resource output while ensuring equality among players. These principles were applied to two-, three-, four-, and five-player cases by using numerical simulations to reproduce realistic configurations and find the best strategies to overcome potential misalignment between the polarization measurement systems of the players. Although a general formula for the N-player case is not presented here, general derivation rules and a verification algorithm are proposed. This report demonstrates the potential usability of quantum states in collective decision making with limited, probabilistic resources, which could serve as a first step toward quantum-based resource allocation systems.

2008 ◽  
Author(s):  
Michel Handgraaf ◽  
Eric van Dijk ◽  
Riël C. Vermunt ◽  
Henk Wilke ◽  
Carsten K. W. De Dreu

Author(s):  
Xinmu Hu ◽  
Xiaoqin Mai

Abstract Social value orientation (SVO) characterizes stable individual differences by an inherent sense of fairness in outcome allocations. Using the event-related potential (ERP), this study investigated differences in fairness decision-making behavior and neural bases between individuals with prosocial and proself orientations using the Ultimatum Game (UG). Behavioral results indicated that prosocials were more prone to rejecting unfair offers with stronger negative emotional reactions compared with proselfs. ERP results revealed that prosocials showed a larger P2 when receiving fair offers than unfair ones in a very early processing stage, whereas such effect was absent in proselfs. In later processing stages, although both groups were sensitive to fairness as reflected by an enhanced medial frontal negativity (MFN) for unfair offers and a larger P3 for fair offers, prosocials exhibited a stronger fairness effect on these ERP components relative to proselfs. Furthermore, the fairness effect on the MFN mediated the SVO effect on rejecting unfair offers. Findings regarding emotional experiences, behavioral patterns, and ERPs provide compelling evidence that SVO modulates fairness processing in social decision-making, whereas differences in neural responses to unfair vs. fair offers as evidenced by the MFN appear to play important roles in the SVO effect on behavioral responses to unfairness.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shion Maeda ◽  
Nicolas Chauvet ◽  
Hayato Saigo ◽  
Hirokazu Hori ◽  
Guillaume Bachelier ◽  
...  

AbstractCollective decision making is important for maximizing total benefits while preserving equality among individuals in the competitive multi-armed bandit (CMAB) problem, wherein multiple players try to gain higher rewards from multiple slot machines. The CMAB problem represents an essential aspect of applications such as resource management in social infrastructure. In a previous study, we theoretically and experimentally demonstrated that entangled photons can physically resolve the difficulty of the CMAB problem. This decision-making strategy completely avoids decision conflicts while ensuring equality. However, decision conflicts can sometimes be beneficial if they yield greater rewards than non-conflicting decisions, indicating that greedy actions may provide positive effects depending on the given environment. In this study, we demonstrate a mixed strategy of entangled- and correlated-photon-based decision-making so that total rewards can be enhanced when compared to the entangled-photon-only decision strategy. We show that an optimal mixture of entangled- and correlated-photon-based strategies exists depending on the dynamics of the reward environment as well as the difficulty of the given problem. This study paves the way for utilizing both quantum and classical aspects of photons in a mixed manner for decision making and provides yet another example of the supremacy of mixed strategies known in game theory, especially in evolutionary game theory.


1986 ◽  
Vol 22 (4) ◽  
pp. 500-508 ◽  
Author(s):  
Chia-chen Chao ◽  
George P. Knight ◽  
Alan F. Dubro

2018 ◽  
Vol 39 (7) ◽  
pp. 3072-3085 ◽  
Author(s):  
Florian Bitsch ◽  
Philipp Berger ◽  
Arne Nagels ◽  
Irina Falkenberg ◽  
Benjamin Straube

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