Agent-based Modeling

Agent-based Modeling (ABM) is a simulation method where the autonomous agents interacting with the environment (space) and/or each other by a set of rules.

The most obvious example of ABM is to simulate actions of non-player characters (NPCs) in computer games.

ABM is able to model heterogeneously, i.e. it does not require the environment to be well stirred (as opposed to ODEs), continuous (as opposed to to PDEs), nor need the characteristics of each kind of agents to be identical (as opposed to SSAs).

This makes ABM more flexible to model individual behaviors. - traffic jam - infectious disease spread - molecular interactions

Elements of ABM

To use Agents.jl, we need to define:

  • The space where the agents live
  • The agents with self-defined properties.
  • The model to hold the space, the agents, and other parameters (called properties)
  • The stepping function step!() to tell how the model evolve.

Could I do ABM by myself?

Yes, you can define the agents, rules and stepping functions from scratch, but it’s more convenient (and perhaps more performant) to use a test package like Agents.jl.

Resources

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