Evoplex: A platform for agent-based modeling on networks
This provides a tool for researchers in fields like evolutionary game theory and computational social science to model complex systems more efficiently, though it is incremental as it builds on existing agent-based modeling and network science approaches.
The authors tackled the need for scalable and user-friendly software for agent-based modeling on networks by developing Evoplex, a fast and extensible platform that enables easy creation, analysis, and replication of experiments.
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.