论文标题
部分可观测时空混沌系统的无模型预测
A mathematical framework for dynamical social interactions with dissimulation
论文作者
论文摘要
建模社交互动是一项艰巨的任务，需要灵活的框架。例如，偏见和外部性是影响此类系统的相关特征，这些功能通常在流行模型中被忽略。本文致力于研究一般数学框架，以理解代理人伪装的社交情况，并且可能对外源客观信息敏感。我们的模型包括参与者可以诚实，有说服力或符合的人群。首先，我们考虑了一个非合作环境，我们在其中建立了游戏的存在，独特性和某些属性。其次，我们分析合作环境，确定帕累托阵线内的最佳策略。在这两种情况下，我们都会开发出数值算法，使我们能够在各种设置下计算评估模型的行为。
Modeling social interactions is a challenging task that requires flexible frameworks. For instance, dissimulation and externalities are relevant features influencing such systems -- elements that are often neglected in popular models. This paper is devoted to investigating general mathematical frameworks for understanding social situations where agents dissimulate, and may be sensitive to exogenous objective information. Our model comprises a population where the participants can be honest, persuasive, or conforming. Firstly, we consider a non-cooperative setting, where we establish existence, uniqueness and some properties of the Nash equilibria of the game. Secondly, we analyze a cooperative setting, identifying optimal strategies within the Pareto front. In both cases, we develop numerical algorithms allowing us to computationally assess the behavior of our models under various settings.
