Asymmetric quantum decision-making

Collective decision-making is crucial to information and communication systems. Decision conflicts among agents hinder the maximization of potential utilities of the entire system. Quantum processes can realize conflict-free joint decisions among two agents using the entanglement of photons or quantum interference of orbital angular momentum (OAM). However, previous studies have always presented symmetric resultant joint decisions. Although this property helps maintain and preserve equality, it cannot resolve disparities. Global challenges, such as ethics and equity, are recognized in the field of responsible artificial intelligence as responsible research and innovation paradigm. Thus, decision-making systems must not only preserve existing equality but also tackle disparities. This study theoretically and numerically investigates asymmetric collective decision-making using quantum interference of photons carrying OAM or entangled photons. Although asymmetry is successfully realized, a photon loss is inevitable in the proposed models. The available range of asymmetry and method for obtaining the desired degree of asymmetry are analytically formulated.

Bandit Algorithm Driven by a Classical Random Walk and a Quantum Walk

Quantum walks (QWs) have the property that classical random walks (RWs) do not possess -- coexistence of linear spreading and localization -- and this property is utilized to implement various kinds of applications. This paper proposes a quantum-walk-based algorithm for multi-armed-bandit (MAB) problems by associating the two operations that make MAB problems difficult -- exploration and exploitation -- with these two behaviors of QWs. We show that this new policy based on the QWs realizes high performance compared with the corresponding RW-based one.