发表机构
Joint Institute for Nuclear Research; Universidade de São Paulo（俄罗斯联合核研究所; 圣保罗大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出兼具概率性、动态性、情感性与异质性的新型动态概率决策网络，以阿莱悖论为例验证其可降低决策误差，还可通过机器学习调控智能体选择。
AI 中文摘要
本文提出了一种新型决策网络并对其运行机制进行分析。该网络的节点由智能体表示，智能体可指代人类等生物个体、大脑神经元或人工智能节点。该网络具有以下特性：一是概率性，每个智能体的选择由相关概率表征；二是动态性，因智能体间的信息交换，概率随时间变化；三是情感性，智能体在备选方案间做选择时会兼顾效用、偏差与情绪；四是异质性，由具有不同属性的智能体群体组成，例如拥有长期记忆和短期记忆的群体。由信息交换引发的网络动态性可降低决策误差，本文以阿莱悖论为例说明网络运行，该例子中网络解决了阿莱悖论并在决策动态过程中随信息交换使决策误差减小。借助机器学习技术，可调控网络智能体的行为，迫使其选择特定备选方案。
英文摘要
A new type of decision networks is suggested and its operation is analyzed. The network nodes are represented by intelligent agents who can denote either some biological beings, like humans, or neurons of the brain, or the nodes of artificial intelligence. The specifics of the network are in the following: It is probabilistic in the sense that the choice, accomplished by each agent, is characterized by the related probability. It is dynamic, with the probabilities varying in time due to the exchange of information between the agents. It is affective, because the agents choose between alternatives by taking account of utility as well as of biases and emotions. In general, it is heterogeneous, being composed of the groups of agents with different properties, for instance having long-term memory and short-term memory. The network dynamics, caused by the information exchange, results in decision error decrease. The network operation is illustrated by the example starting with the Allais paradox, its resolution, and the decision error diminution in the process of decision dynamics with information exchange. Resorting to machine-learning techniques it is possible to regulate the behavior of the network agents forcing them to choose particular alternatives.
CommentsLatex file, 41 pages, 10 figures
Journal refPhysica A 687 (2026) 131382
