Modeling and Simulating Emerging Behaviour in Spatial Systems with Cell-DEVSSpeaker: Gabriel Wainer – Ottawa, ON, Canada
Topic(s): Applied Computing
In recent years, new methodologies have allowed building agent-based simulation software executing on grid-shaped cell spaces. There have been numerous efforts integrating agents and cellular models for simulation, in which we can model agents that have emerging behavior that can represent intelligent systems. We have defined a new methodology for modeling such cell-based agent models using a formal modeling technique that permits defining each cell in a cell space as individual independent entity, called Cell-DEVS. The goal of Cell-DEVS is to build discrete-event cell spaces, improving their definition by making the timing specification more expressive and the definition of complex models simpler.
We will introduce the main characteristics of the Cell-DEVS formalism, and will show how to model complex cell spaces using this methodology. We will present different examples of application, and discuss open research issues in this area, focusing on models with emerging behaviour that can be used in AI applications. We will then show some examples of the current use of DEVS, including applications in different fields. We will introduce an integrated environment that deals with these issues, orchestrating a cellular-based simulator (CD++), a GIS and data visualization, to simulate behavior and analyze results supporting the decision making for varied environmental scenarios. The limitations above are solved by adding raw simulation results into the georeferenced maps, associating many sources of information (even if they do not come from the simulation model), providing a more powerful analysis experience. The simulation model is fed by the GIS with updated data, while the model design process enables integrating additional information layers. The methodology uses a cellular modeling approach in which each cell is defined as a discrete event agent, and defines a procedure to couple cells evolving the state of the influenced neighbors. We will also discuss models of spiking neurons, data mining and market evolution, between others.
About this LectureNumber of Slides: 40
Duration: 40 - 120 minutes
Languages Available: English
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