Preferences, fundamental in all forms of strategic behavior and collective decision-making, in their raw form, are an abstract ordering on a set of alternatives. Agents, we assume, revise their preferences as they gain more information about other agents. Exploiting the ordered algebraic structure of preferences, we introduce a message-passing algorithm for heterogeneous agents distributed over a network to update their preferences based on aggregations of the preferences of their neighbors in a graph. We demonstrate the existence of equilibrium points of the resulting global dynamical system of local preference updates and provide a sufficient condition for trajectories to converge to equilibria: stable preferences. Finally, we present numerical simulations demonstrating our preliminary results.

翻译：偏好作为所有策略性行为与集体决策的基础，其原始形式是对备选方案集合的抽象排序。我们假设智能体在获取关于其他智能体的更多信息时会修正自身偏好。利用偏好序的代数结构特性，我们提出了一种面向网络中异构智能体的消息传递算法，该算法基于图中邻居偏好的聚合结果更新自身偏好。我们证明了局部偏好更新构成的全局动态系统存在平衡点，并给出了轨迹收敛到平衡态的充分条件——即稳定偏好。最后，通过数值仿真验证了初步研究结果。