IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

摘要

在这篇短文中,我们研究了经典的弹簧双质量系统的信息论类比,它产生于对代理人系统学习理论中弗里斯顿自由能原理的物理解释。利用流形上的经典力学方法,我们用分布上的费雪度量定义了一个动能项,并用代理人信念上的压力定义了一个势能函数。由此产生的拉格朗日(哈密顿)产生了经典德格鲁特动力学的一种变体。在双代理情况下,势函数使用杰弗里发散定义,由此产生的动力学具有非线性弹簧的特征。这些动力学产生的轨迹类似于环上的流动,但数值显示会在空间边界附近产生混沌。然后,我们将劝说作为一个信息论控制问题进行研究,分析表明,与提供一个接近目标的缓慢变化的信念状态相比,操纵具有固定目标的同伴压力是一种更稳定的改变代理信念的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamics of an information theoretic analog of two masses on a spring

In this short communication we investigate an information theoretic analogue of the classic two masses on spring system, arising from a physical interpretation of Friston’s free energy principle in the theory of learning in a system of agents. Using methods from classical mechanics on manifolds, we define a kinetic energy term using the Fisher metric on distributions and a potential energy function defined in terms of stress on the agents’ beliefs. The resulting Lagrangian (Hamiltonian) produces a variation of the classic DeGroot dynamics. In the two agent case, the potential function is defined using the Jeffrey’s divergence and the resulting dynamics are characterized by a non-linear spring. These dynamics produce trajectories that resemble flows on tori but are shown numerically to produce chaos near the boundary of the space. We then investigate persuasion as an information theoretic control problem where analysis indicates that manipulating peer pressure with a fixed target is a more stable approach to altering an agent’s belief than providing a slowly changing belief state that approaches the target.

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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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