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In our model, agents are embedded in a network with a varying number of neighbors.
In our model, agents are initialized as non-labeled agents, i.e. they are considered as newcomers.
Within the architecture of the model, agents are classified as active or passive.
In this model, agents are defined by network nodes and represent brain regions, and links representing functional connectivity between nodes dictate which agents interact.
In the initialization of the model, agents are randomly distributed and consequently most of spatial distribution samples have agents of both tags dispersed in the lattice, but close enough to make the dynamics interdependent.
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In brief, simulated individuals (the model "agents") were assigned a diathesis value and their exposure to stress was represented by movement of those agents across an environment characterized by different levels of stress.
The components of the performance analysis agent, one of the human modeling agents are described and their characteristics for applying in manufacturing systems are explained.
In corresponding agent-based models, agents are not real people but "computational objects modeled as interacting according to rules"... "whose micro-level interactions create emergent patterns" in space and time.
In most states, a model agency, and/or model agent, is normally required to possess a state license.
What I'm saying – and saying to you especially Mr Smug Modelling Agent – is that this is about practicality.
When defining an agent-based model, many agents are created and put in relation to one another to form the system over which they will evolve.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com