Quantum Reachability Games

IF 6 3区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Wuniu Liu;Zhihui Li;Yongming Li
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引用次数: 0

Abstract

The reachability of quantum games refers to the ability of two players to reach a certain subspace of Hilbert spaces in a quantum game modeled by a newly proposed quantum game process (QGP). We refer to this as quantum reachability games (QRGs). Reachability analysis is crucial in studying the strategic behavior and decision-making processes of players in quantum games, as it aids in devising optimal strategies to achieve desired objectives. In a QRG, players make decisions based on their quantum strategies related to decision epochs, which are represented by quantum operations or quantum measurements. We present an algorithm for evaluating two-player strategies, and investigate the optimal QRG for two players, where the goal of player 1 is to maximize his/her probability of reaching a given target subspace, while player 2 aims to minimize it. We show that any optimal QRG are determined, i.e., both of the two players have the same probability of winning in non-cooperative reachability games. Furthermore, our results also demonstrate that reachability games in the quantum world can be undecidable in certain cases. These findings are significantly distinct from those in the probabilistic or classical scenarios. Finally, we present three case studies, penny flipover, ambushing quantum walk and peer-to-peer scheme game on quantum network, to illustrate the potential applications and implications of QRGs.
量子可达性游戏
量子博弈的可达性是指用一种新提出的量子博弈过程(QGP)建模的量子博弈中,两个参与者到达希尔伯特空间的某一子空间的能力。我们将其称为量子可达性游戏(qrg)。可达性分析在研究量子博弈参与者的战略行为和决策过程中至关重要,因为它有助于设计实现预期目标的最佳策略。在QRG中,玩家根据与决策时代相关的量子策略做出决策,决策时代由量子操作或量子测量表示。我们提出了一种评估两参与人策略的算法,并研究了两参与人的最佳QRG,其中参与人1的目标是最大化他/她到达给定目标子空间的概率,而参与人2的目标是最小化它。我们证明了任何最优QRG都是确定的,即在非合作可达性博弈中,两个参与者都具有相同的获胜概率。此外,我们的结果还表明,在某些情况下,量子世界中的可达性博弈可能是不可确定的。这些发现与概率或经典情景中的发现明显不同。最后,我们通过量子网络上的便士翻转、伏击量子行走和点对点方案博弈三个案例来说明QRGs的潜在应用和意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
10.30
自引率
7.50%
发文量
147
期刊介绍: The IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI) publishes original articles on emerging aspects of computational intelligence, including theory, applications, and surveys. TETCI is an electronics only publication. TETCI publishes six issues per year. Authors are encouraged to submit manuscripts in any emerging topic in computational intelligence, especially nature-inspired computing topics not covered by other IEEE Computational Intelligence Society journals. A few such illustrative examples are glial cell networks, computational neuroscience, Brain Computer Interface, ambient intelligence, non-fuzzy computing with words, artificial life, cultural learning, artificial endocrine networks, social reasoning, artificial hormone networks, computational intelligence for the IoT and Smart-X technologies.
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