引入类量子影响图以解决违反确定性原理的问题
Introducing Quantum-Like Influence Diagrams for Violations of the Sure Thing Principle
摘要：
这是这项工作的重点，扩展和研究以前提出的量子贝叶斯网络，以处理决策的情况下，将最大期望效用的概念，在影响图。一般的想法是利用类量子贝叶斯网络中产生的量子干涉项来影响用于计算某些行为的预期效用的概率。这样，我们就不是在提出一种新的期望效用假设。相反，我们把它保持在它的经典定义之下。我们只是将其作为概率图模型的扩展，用一种称为影响图的紧凑图形表示，其中效用函数取决于类量子贝叶斯网络的概率影响。我们的研究结果表明，拟议的量子影响图确实可以利用量子贝叶斯网络的量子干涉效应，以最大限度地提高效用的合作行为，在一个完全理性的缺陷行为下的囚徒困境游戏。
英文摘要：
It is the focus of this work to extend and study the previously proposed quantum-like Bayesian networks to deal with decision-making scenarios by incorporating the notion of maximum expected utility in influence diagrams. The general idea is to take advantage of the quantum interference terms produced in the quantum-like Bayesian Network to influence the probabilities used to compute the expected utility of some action. This way, we are not proposing a new type of expected utility hypothesis. On the contrary, we are keeping it under its classical definition. We are only incorporating it as an extension of a probabilistic graphical model in a compact graphical representation called an influence diagram in which the utility function depends on the probabilistic influences of the quantum-like Bayesian network. Our findings suggest that the proposed quantum-like influence digram can indeed take advantage of the quantum interference effects of quantum-like Bayesian Networks to maximise the utility of a cooperative behaviour in detriment of a fully rational defect behaviour under the prisoner's dilemma game.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
