A generalized voter model with time-decaying memory on a multilayer network

Liu, Zhong; Xu, Wei; Chen, Rong-Da; Zhong, Chen-Yang; Qiu, Tian; Shi, Yongdong; Wang, Liliang

doi:10.1016/j.physa.2016.03.089

Cited by 5 publications

(2 citation statements)

References 64 publications

(63 reference statements)

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“…Different idea of memory has been proposed by Takaguchi and Masuda, who endowed links, instead of voters, between the nodes with a random variable, which represented the time until the initial update event occurs on this link [17]. Zhong et al have introduced a generalized voter model with timedecaying rate of the influence of peer pressure, which incorporates a multilayer network and memory of past influences [18].…”

Section: Introductionmentioning

confidence: 99%

Impact of memory on opinion dynamics

Jędrzejewski

Sznajd-Weron

2018

Physica A: Statistical Mechanics and its Applications

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We investigate an agent-based model of opinion dynamics with two types of social response: conformity and independence. Conformity is introduced to the model analogously as in the Sznajd model or q-voter model, which means that only unanimous group exerts peer pressure on individuals. The novelty, in relation to previous versions of the q-voter model, is memory possessed by each agent and external noise T , which plays the role of social temperature. Each agent has its own memories of past experiences related to the social costs and benefits of being independent or conformist. If an agent was awarded in past more for being independent, it will have a greater tendency to be independent than conformist and vice versa. We will show that depending on the social temperature T the system spontaneously organizes into one of two regimes. Below a certain critical social temperature T c , all agents in the society acquire personal traits (so called person state). Some of them become permanent conformists and others start to behave forever independently. This means that initially homogeneous population becomes heterogeneous, and agents respond differently to social influence. For T > T c , all agents with equal probabilities behave independently or conform to peer pressure (so called situation state). This regime change between person and situation state, which reminds the idea of an annealed vs. quenched disorder, affects also public opinion. Particularly interesting results are obtained for individualistic societies, in which public opinion is non-monotonic function of T , which means that there is an optimal social temperature for which an agreement in the society is the highest.

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Section: Introductionmentioning

confidence: 99%

Impact of memory on opinion dynamics

Jędrzejewski

Sznajd-Weron

2018

Physica A: Statistical Mechanics and its Applications

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“…We note that the authors find a similar result to the one here, namely, the addition of memory speeds up the convergence of their agents. There is also a generalization of the voter model (Zhong et al 2016) which considers agents with memory of past states. In their protocol and topologies studied, the authors find memory to be detrimental to consensus.…”

Section: Related Workmentioning

confidence: 99%

The Influence of Memory in Multi-Agent Consensus

Marzagão

Bonatto

Madeira

et al. 2021

AAAI

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Multi-agent consensus problems can often be seen as a sequence of autonomous and independent local choices between a finite set of decision options, with each local choice undertaken simultaneously, and with a shared goal of achieving a global consensus state. Being able to estimate probabilities for the different outcomes and to predict how long it takes for a consensus to be formed, if ever, are core issues for such protocols. Little attention has been given to protocols in which agents can remember past or outdated states. In this paper, we propose a framework to study what we call `memory consensus protocol'. We show that the employment of memory allows such processes to always converge, as well as, in some scenarios, such as cycles, converge faster. We provide a theoretical analysis of the probability of each option eventually winning such processes based on the initial opinions expressed by agents. Further, we perform experiments to investigate network topologies in which agents benefit from memory on the expected time needed for consensus.

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