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X-Machines for Agent-Based Modeling: FLAME Perspectives
• Source agent. The source agent is producing new protein agents. The
source will also be decaying after a certain time period to reduce its life
and eventually disappear or stop producing proteins.
• Protein agent. The protein agents are diffusing across the compartment
depending on the protein concentration in the compartment it is in.
• Compartment agent. To depict the embryo as a whole, a hundred compartment agents can be used to determine the concentration of proteins
within them. This agent can be avoided as the compartments themselves
are not doing any function, but can be used to account for the result
analysis later. Alternatively, one agent representing the environment can
also be used, thus showing that it depends on modeler perspectives on
how the model is written.
Figure 7.6 shows the activities during one iteration of the model. In addition, messages such as the Protein posts location, which are outputs a protein
location message which is read by other proteins or compartment agents, not
shown. This message would be the input to the functions for Protein agent
to calculate the next move or for the Compartment agent to count how many
proteins it has.
FIGURE 7.6: Agent activities during one iteration.
The model was executed for 12,000 iteration steps, assuming one time step
represents one second of the diffusion model (in the stochastic method), with
X-Machines for Agent-Based Modeling: FLAME Perspectives
• Source agent. The source agent is producing new protein agents. The
source will also be decaying after a certain time period to reduce its life
and eventually disappear or stop producing proteins.
• Protein agent. The protein agents are diffusing across the compartment
depending on the protein concentration in the compartment it is in.
• Compartment agent. To depict the embryo as a whole, a hundred compartment agents can be used to determine the concentration of proteins
within them. This agent can be avoided as the compartments themselves
are not doing any function, but can be used to account for the result
analysis later. Alternatively, one agent representing the environment can
also be used, thus showing that it depends on modeler perspectives on
how the model is written.
Figure 7.6 shows the activities during one iteration of the model. In addition, messages such as the Protein posts location, which are outputs a protein
location message which is read by other proteins or compartment agents, not
shown. This message would be the input to the functions for Protein agent
to calculate the next move or for the Compartment agent to count how many
proteins it has.
FIGURE 7.6: Agent activities during one iteration.
The model was executed for 12,000 iteration steps, assuming one time step
represents one second of the diffusion model (in the stochastic method), with