Cellular Automata DEVS: A Modeling, Simulation, and Visualization Environment

Cellular Automata (CA) models are represented as a collection of independent dynamical cells having some specific spatial relationship to each other. These tessellation automata can have simple to complex behaviors due to both individual cell behaviors as well as their interactions. Code debugging, supported by advanced software development tools, is needed for developing CAs owing their complex dynamics to cells that have non-trivial event handling and timing. As such, it is useful to debug models during simulation through step-by-step examination of any number of cells using rich control and visualization means. In this paper, we show the CA-DEVS framework where cell and Cellular Automata models are derived from atomic and coupled Parallel DEVS models. This framework uniquely supports visualizations using run-time generation of input, output, and state linear and superdense time trajectories as well as run-time spatial animation with playback. Multimodal visualization capabilities allow examining behavior of any number of cells independent of any other cell. We describe some key parts of the architectural design of the CA-DEVS and highlight some ongoing and future research.

[1]  Richard J. Gaylord,et al.  Modeling Nature: Cellular Automata Simulations with Mathematica® , 1996 .

[2]  Glen E. P. Ropella,et al.  Toward modular biological models: defining analog modules based on referent physiological mechanisms , 2014, BMC Systems Biology.

[3]  Lev Naumov CAME &L-Cellular Automata Modeling Environment & Library , 2004, ACRI.

[4]  Stephen Wolfram,et al.  A New Kind of Science , 2003, Artificial Life.

[5]  Bernard P. Zeigler,et al.  Theory of Modeling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems , 2000 .

[6]  Jörg R. Weimar,et al.  JCAsim - a Java System for Simulating Cellular Automata , 2000, ACRI.

[7]  Gabriel A. Wainer,et al.  Discrete-Event Modeling and Simulation: A Practitioner's Approach , 2009 .

[8]  Stephen Wolfram,et al.  Cellular automata as models of complexity , 1984, Nature.

[9]  Sean Luke,et al.  MASON: A Multiagent Simulation Environment , 2005, Simul..

[10]  Hessam S. Sarjoughian,et al.  DEVS-suite: a simulator supporting visual experimentation design and behavior monitoring , 2009, SpringSim '09.

[11]  Master Gardener,et al.  Mathematical games: the fantastic combinations of john conway's new solitaire game "life , 1970 .

[12]  Hessam S. Sarjoughian,et al.  Building Simulation Modeling Environments Using Systems Theory and Software Architecture Principles , 2004 .

[13]  Gabriel A. Wainer,et al.  CD++Modeler: a graphical toolkit to develop DEVS models , 2008, SpringSim '08.

[14]  Gabriel A. Wainer CD++: a toolkit to develop DEVS models , 2002, Softw. Pract. Exp..

[15]  Hessam S. Sarjoughian,et al.  Building a hybrid DEVS and GRASS model using a composable cellular automaton , 2016, Int. J. Model. Simul. Sci. Comput..

[16]  Hessam S. Sarjoughian,et al.  Composable Cellular Automata , 2009, Simul..

[17]  Xiaolin Hu,et al.  DEVS-FIRE: Towards an Integrated Simulation Environment for Surface Wildfire Spread and Containment , 2008, Simul..

[18]  Gabriel A. Wainer,et al.  Application of the Cell-DEVS Paradigm for Cell Spaces Modelling and Simulation , 2001, Simul..

[19]  Hessam S. Sarjoughian,et al.  Superdense time trajectories for DEVS simulation models , 2015, SpringSim.

[20]  Hessam S. Sarjoughian,et al.  Experimental socioecology: Integrative science for anthropocene landscape dynamics , 2016 .