Agent-based simulations are used to understand disease transmission, the spread of social unrest, and the propagation a host of other contagions such as fads, rumors, and influence. Contagions may be spread, for example, by face-to-face interaction
and/or electronic means (e.g., social media).
Simulation is an effective way to study these dynamics of contagion spread. Often simulations are carried out on populations that are represented as networks, where vertices represent agents (e.g., people) and edges represent their interactions. Typically, populations are composed of thousands, millions, or even billions of agents, with the result that only a small fraction of the possible dynamics can be evaluated.
Understanding of system dynamics, provides insights on how to control them. Examples include: How to minimize the spread of epidemics. How to increase the probability that a marketing campaign goes viral. How to spread safety tips among drug users. How to encourage healthy youth behavior (e.g., avoid smoking, excessive drinking).
We model populations of (human) agents and their interactions. Translation from reality to model:
Graph of nodes, each has a state. Vertex Functions quantifies when a node changes state, and to what state, based on its neighborhood. Update Scheme defines the ordering of execution the functions. Update Scheme can be sequential: Nodes update one-at-a-time in a prescribed order. Synchronous: Nodes update simultaneously. Block sequential: generalizes the other two. A primary use: compute phase space. Set of all state transitions for all possible system states.
The Graph Dynamical Systems Calculator (GDSCalc) is a web-based application within the CINET suite. Unlike most simulators, GDSCalc computes all of the dynamics for a given system, which are represented as a phase space. Consequently, it operates on much smaller networks. GDSCalc provides a user interface to select or create networks, assign models to vertices that describe their behavior, and specify the order in which the dynamics are processed; it also manages data and jobs across users. A computational engine performs the calculations on a cluster, and results are displayed textually and graphically. One of the primary uses of GDSCalc is experimental mathematics, where computed behaviors for smaller networks provide direction for theoretical characterizations of systems in general, even systems with billions of agents.
Video 1: Creating Graphs in list view
Video 2: Drawing graphs
Video 3: Assign model (vertex function) for each node
Video 4: Defining the update scheme, the order in which dynamics are processed
Video 5: Defining the nodes initial states
Video 6: Viewing results
Video 7: Loading existing analysis
Video 8: Using the admin tab for regression testing
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