ArticleScientific reports2020
Entangled N-photon states for fair and optimal social decision making.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 13 citations in OpenAlex.
- Conflict-free joint decision by lag and zero-lag synchronization in laser network.Scientific reports · 2024Article
- Decision making for large-scale multi-armed bandit problems using bias control of chaotic temporal waveforms in semiconductor lasers.Scientific reports · 2022Article
- Conflict-free collective stochastic decision making by orbital angular momentum of photons through quantum interference.Scientific reports · 2021Article
- Entangled and correlated photon mixed strategy for social decision making.Scientific reports · 2021Article
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Authors and funding
6 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Situations 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.
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