Goal Seeking Archetype

The goal seeking structure endeavors to bring a balance between a current state and a desired state. This is one of the two foundation archetypes. The other being the growth structure. There is also a video for this model which is component of the Systems Archetypes Course.

The goal seeking structure endeavors to bring a balance between a current state and a desired state. This is one of the two foundation archetypes. The other being the growth structure. There is also a video for this model which is component of the Systems Archetypes Course.
The goal seeking structure begins with a [desired state] and a [current state] the difference between which creates a [gap].
The [gap] then serves as an impetus for [action] which is intended to move the [current state] in the direction of the [desired state] reducing the [gap]. As the [gap] gets smaller [action] gets smaller though [current state] continues to move toward the [desired state]. When [current state] equals [desired state] the [gap] is zero and no more action is required.
The structure demonstrates a goal seeking behavior which is the emergent characteristic of the structure. None of the elements alone exhibit this behavior.
Any situation where [action] is taken to move something toward a [desired state] is a goal seeking structure. Goal seeking structures may have many elements though you can tell a goal seeking structure because there are an odd number of subtracts from / opposite influences in the loop.
The simulation structure is the same as the causal loop except for the addition of an [action factor] which can be varied from 0 to 1 to influence variations in action.
If we simulate the goal seeking structure in a generic form with [desired state] = 1, [current state] = 0, and [action factor] = 1 we find that the [desired state] is reached in one time step. This is probably a bit unrealistic for most real situations.
If we set [action factor] = 0.5 meaning that only 50% of the gap is the applied [action] the results are quite different. [action factor] essentially represents the constraint on the resources necessary to perform the action. The choppy nature of the graph is because the Simulation Time Step is set to 1.
Please spend some time running the simulation with different initial values to get a sense of the behavior of the Goal Seeking structure. Also change the values for the Simulation Time Step in Settings to see what effect that has. Can you explain why?

View the model in Insight Maker