Peer-Reviewed Journal Details
Mandatory Fields
Cardinot, M;O'Riordan, C;Griffith, J;Perc, M
2019
January
Softwarex
Evoplex: A platform for agent-based modeling on networks
Published
Optional Fields
SIMULATION SYSTEMS
9
199
204
Agent-based modeling and network science have been used extensively to advance our understanding of emergent collective behavior in systems that are composed of a large number of simple interacting individuals or agents. With the increasing availability of high computational power in affordable personal computers, dedicated efforts to develop multi-threaded, scalable and easy-to-use software for agent-based simulations are needed more than ever. Evoplex meets this need by providing a fast, robust and extensible platform for developing agent-based models and multi-agent systems on networks. Each agent is represented as a node and interacts with its neighbors, as defined by the network structure. Evoplex is ideal for modeling complex systems, for example in evolutionary game theory and computational social science. In Evoplex, the models are not coupled to the execution parameters or the visualization tools, and there is a user-friendly graphical interface which makes it easy for all users, ranging from newcomers to experienced, to create, analyze, replicate and reproduce the experiments. (C) 2019 The Authors. Published by Elsevier B.V.
2352-7110
10.1016/j.softx.2019.02.009
Grant Details
Publication Themes