Experimenting with Agent-Based Model Simulation Tools

Abstract

Agent-based models (ABMs) are one of the most effective and successful methods for analyzing real-world complex systems by investigating how modeling interactions on the individual level (i.e., micro-level) leads to the understanding of emergent phenomena on the system level (i.e., macro-level). ABMs represent an interdisciplinary approach to examining complex systems, and the heterogeneous background of ABM users demands comprehensive, easy-to-use, and efficient environments to develop ABM simulations. Currently, many tools, frameworks, and libraries exist, each with its characteristics and objectives. This article aims to guide newcomers in the jungle of ABM tools toward choosing the right tool for their skills and needs. This work proposes a thorough overview of open-source general-purpose ABM tools and offers a comparison from a two-fold perspective. We first describe an off-the-shelf evaluation by considering each ABM tool’s features, ease of use, and efficiency according to its authors. Then, we provide a hands-on evaluation of some ABM tools by judging the effort required in developing and running four ABM models and the obtained performance.

Reliable and Efficient Agent-Based Modeling and Simulation

“…Table 1 summarizes the ABM frameworks and tools described, emphasizing whether they provide support for the most relevant features. The last two rows of the table show the declared efficiency and ease of use for each tool as discussed in the survey by Antelmi et al (2023). Specifically, the term ease of use refers to the effort required for installation and setup procedures, the presence of examples, and the clarity of the documentation provided.…”

Spatial Agent-Based Modelling and Simulation to Evaluate on Public Policies for Energy Transition

“…While the behavior and individual actions of agents are defined on the micro level, the resulting model is able to show patterns and behaviors on the macro level that were not explicitly defined, but rather evolved during the execution of the model ("bottom-up" approach) [1,2,3,4,5,8,9]. By using GIS data, ABMs are able to incorporate real world geospatial data into the simulation to define the area in which the agents can move and act within [10]. Such an environment could consist of spatial grids, continuous spaces, or networks.…”

Overview of Software Agent Platforms Available in 2023

“…Others, such as [107], assess the existing (at the time of writing) platforms from the perspective of the system structure and the supported methodology. There are also reviews, such as [108], that focus mainly on the platforms that can be used for educational and teaching purposes.…”

“…However, as the emphasis is put on agent-based modeling and simulations, this work does not provide an in-depth analysis of platforms that could be applied in other fields. An example of a more recent study that follows this approach is [108,113].…”