CppyABM : An open‐source agent‐based modeling library to integrate C++ and Python

The present work provides an open-source, agent-based behavioral model primarily addressed to the dynamics associated with the commodities spot price formation, as well as variations and contrast patterns belonging to the exchanged quantity. The framework can flexibly be used for several commodities, but it has to be integrated and qualified with the modelization of producers’ and buyers’ behavior when used for the analysis of a specific commodity, stock, or group of merchandise. Due to the fact that various commodities or consumer artifacts are perceived and treated differently in several diverse contexts, the intended tasks or functions are mainly entrusted to those experts in the specific fields, who would find the software tool we designed a good starting point for their investigations. Toward achieving this aim, open-source code is provided along with detailed documentation on how to use, further develop, and enhance the present features of the proposed agent-based modeling and simulation software. This is publicly available at https://github.com/gfgprojects/cms

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abmR: an R package for agent-based model analysis of large-scale movements across taxa

10.1101/2021.09.15.460374 ◽

2021 ◽

Author(s):

Benjamin Gochanour ◽

Javier Fernández-López ◽

Andrea Contina

Keyword(s):

Open Source ◽

Disease Ecology ◽

Large Scale ◽

Animal Movement ◽

R Package ◽

Theoretical Background ◽

Agent Based Modeling ◽

List Type ◽

Agent Based ◽

Continental Scale

AbstractAgent-based modeling (ABM) shows promise for animal movement studies. However, a robust, open-source, and spatially explicit ABM coding platform is currently lacking.We present abmR, an R package for conducting continental-scale ABM simulations across animal taxa. The package features two movement functions, each of which relies on the Ornstein-Uhlenbeck (OU) model.The theoretical background for abmR is discussed and the main functionalities are illustrated using two example populations.Potential future additions to this open-source package may include the ability to specify multiple environmental variables or to model interactions between agents. Additionally, updates may offer opportunities for disease ecology and integration with other R movement modeling packages.

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