CellNet: a Hands-on Approach for Agent-based Modeling and Simulation

CellNet is a free to use open-source Java-based software, developed by Juan C. Burguillo and licensed under the GNU Lesser General Public License (LGPL). CellNet is a research resource created by the author to study multi-agent systems, evolutionary game theory and cellular automata simulations. Since then, it has been used in a number of research works by the author, Ph.D. students and some research colleagues from other Universities.

You can find next the installing instructions, documentation and related material.

Try out the CellNet simulator in a one-shot run

If you want to try out quickly the simulator, just download the CellNet.jar file, and do a double quick or execute it from the shell. Note that you must have the Java 1.8 version installed in your system.

CellNet Basic Features

CellNet has its origins in 2003, a time were most of the simulators were too complex or do not provide enough tools to comfortably manage cellular automata networks and evolutionary game theory simulations in Java with user-friendly interfaces.

CellNet works in two modes: i) using a graphical user interface (GUI) for doing micro-simulations or ii) using a batch mode for doing macro-simulations. CellNet also provides support for:

  • Visualizing the whole set of cells and their state along each simulation iteration.
  • Visualizing the simulation results in real time at each iteration. A set of graphical windows are provided for every relevant simulation result.
  • Importing network data to reuse particular network structures to run experiments.
  • Exporting network data, to save a particular network structure. The format used for the exported files is compatible with popular network analyzers such as Pajek or Gephi.

A CellNet snapshot with the coalition spatial IPD game

General Configuration Window

Network Parameter Window

Payoff Matrix Window

Coalition Spatial IPD Game Parameter Window

CellNet Role in the Book "Self-organizing Coalitions for managing Complexity"

CellNet allows a hands-on approach to simulating and modifying most of the coalition-based experiments presented in the book:

Self-organizing Coalitions for Managing Complexity by J.C. Burguillo, that appeared in the Springer ECC series (Emergence, Complexity and Computation 29). ©Springer Nature 2018. https://doi.org/10.1007/978-3-319-69898-4

Following the book, the readers can test the simulations by means of:

  • Running Micro-simulations: most of the experiments described in the research chapters (except the ones from chapter 10 about Electrical Vehicles and SmartGrids, which were programmed in Netlogo) can be directly run in a one-shot mode, selecting them directly from the main menu of the simulator. The different game simulation parameters can be reviewed and modified from the experiment option window, or from a general configuration window. No programming skills are needed to run the simulator in this mode, so the reader can explore the contents of the book, repeat some experiments or perform new ones by just selecting different parameter values.
  • Running Macro-simulations: having very basic general programming skills allows the reader to configure some batch files to execute a set of experiments, involving multiple runs, to analyze the average results provided by such set of game simulations.
  • Modifying the algorithms: readers having standard Java programming skills can redesign their own algorithms, and then test the behaviors obtained by performing new experiments. For this, new algorithms can be created from scratch, or more commonly, the algorithm files already included can be inherited and used as templates. CellNet code includes support for generating different types of complex topologies, using several machine learning techniques, performing evolutionary meta-decisions, generating real-time visualizations and interacting with external network analyzers.