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A rule base, driven by experimental findings, governs the behavior of individual agents.
Moreover, instead of the current approach of using input-output behavior of individual agents, the model allows the behavior to be parametrized in terms of variables that represent aggregated behavior of large numbers of agents.
One approach to modeling multi-agent systems (MASs) is to employ a method that defines components which describe the local behavior of individual agents, as well as a special component, called a coordinator.
While agents within a class will have the same rules for behavior, the behavior of individual agents varies because of differences in local conditions.
Agent-based models follow a bottom-up simulation strategy, defining simple rules that govern the behavior of individual agents (the cells, in our case) without a global view of the whole system.
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This is because it can represent important phenomena resulting from the characteristics and behaviors of individual agents and their interactions (Railsback & Grimm 2012).
ABM is a discrete modeling approach that enables the simulation of the behaviors of individual agents, or in this case, cells and their sub-cellular compartments, within a heterogeneous environment over time.
More precisely the problem here is to understand how local laws describing the behavior of the individual agents influence the global behavior of the networked system.
The ABM, therefore, represents the collection of individual agent behaviors that emerge as they individually interact with one another and with their dynamic environment.
He and others have begun to develop so-called agent-based models of the economy, asking in effect how the seemingly random behavior of individual ants can give rise to anthills with all their pulsing purpose, form and intelligence.
There are many potential decision-making functions in a GKD process and they have a different effect on the behavior of an individual agent and the performance of the overall system.
More suggestions(21)
behavior of relevant agents
behavior of certain agents
behavior of individual operators
behavior of relevant agents
behavior of adaptive agents
behavior of individual transcripts
behavior of individual recipients
behavior of disaggregated agents
behavior of individual organisms
behavior of individual workers
behavior of multiple agents
behavior of natural agents
behavior of individual molecules
behavior of individual bubbles
behavior of individual faults
behavior of individual animals
behavior of individual franchises
behavior of individual drivers
behavior of individual superfamilies
behavior of dietary agents
behavior of individual users
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com