Agents.jl: agent-based modeling framework in Julia

Vahdati, Ali R.

doi:10.21105/joss.01611

Cited by 16 publications

(9 citation statements)

References 6 publications

(5 reference statements)

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“…For our simulations, this is especially true now that a dedicated Julia package for agent-based modeling has been developed, to wit, the Agents.jl package, information about which can be found here: https://github.com/JuliaDynamics/Agents.jl; see also Vahdati (2019). The package offers a generic framework geared toward making any agent-based modeling easy by requiring from the user only a specification of agent and model properties.…”

Section: Appendixmentioning

confidence: 99%

Mis- and disinformation in a bounded confidence model

Douven

Hegselmann

2021

Artificial Intelligence

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The bounded confidence model has been widely used to formally study groups of agents who are sharing opinions with those in their epistemic neighborhood. We revisit the model with an eye toward studying mis-and disinformation campaigns, which have been much in the news of late. To that end, we introduce typed agents into the model, specifically agents who can be irresponsible in different ways, most notably, by being deceitful, but also by being reluctant to try and obtain information from the world directly. We further add a mechanism of confidence dynamics to the model, which-among other things-allows agents to adapt the closeness threshold for counting others as being their epistemic neighbors. This will be used to study the effectiveness of possible defense mechanisms against mis-and disinformation efforts.

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Section: Appendixmentioning

confidence: 99%

Mis- and disinformation in a bounded confidence model

Douven

Hegselmann

2021

Artificial Intelligence

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“…In addition to these already popular packages, Mesa (2020) is a Python-based agent-based software toolkit that has recently become increasingly popular, partially due to the popularity of the Python language. Lately, several researchers also use the Julia framework for ABM (e.g., Basurto et al 2020; for a corresponding software package, see Vahdati 2019). The previously mentioned network CoMSES (2020) includes a computational model library, access to an active community, and various educational resources.…”

Section: Softwarementioning

confidence: 99%

Agent‐based modeling of new product market diffusion: an overview of strengths and criticisms

Rand

Stummer

2021

Ann Oper Res

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Market diffusion of new products is driven by the actions and reactions of consumers, distributors, competitors, and other stakeholders, all of whom can be heterogeneous in their individual characteristics, attitudes, needs, and objectives. These actors may also interact with others in various ways (e.g., through word of mouth or social influence). Thus, a typical consumer market constitutes a complex system whose behavior is difficult to foresee because stochastic impulses may give rise to complex emergent patterns of system reactions over time. Agent-based modeling, a relatively novel approach to understanding complex systems, is well equipped to deal with this complexity and, therefore, may serve as a valuable tool for both researchers studying particular market effects and practitioners seeking decision support for determining features of products under development or the appropriate combination of measures to accelerate product diffusion in a market. This paper provides an overview of the strengths and criticisms of such tools. It aims to encourage researchers in the field of innovation management, as well as practitioners, to consider agent-based modeling and simulation as a method for gaining deeper insights into market behavior and making better-informed decisions.

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“…Recently, Julia-based Agents.jl has emerged, promising to combine the convenience of data manipulation and analysis with the power of scalable computing and simulation offered by type-stable compiled languages (Vahdati, 2019).…”

Section: Habitat (Spatial Models For Waterfowl Movement)mentioning

confidence: 99%