I'm a software engineer and as a side project I'm creating an ant simulator. When I say "ant simulator" I mean just that -
I'm not attempting to create an application that uses / benefits from ACOA (Ant Colony Optimization Algorithms), but rather an application that attempts to accurately, as best as I can understand / research provides, model the behavior of ants.
For example, my research shows that foraging ants return to the nest in a more direct path once they find their food instead of following the more random trail back.
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I can easily assume that the ant will always do this and it will yield a 100% shortest route from the ant's current position to the nest, but I don't think ants "behaviorally" are capable of those calculations.
So my question is how do they deterministically normalize their return path? Do they normalize based on any path intersections from their original? If so this would yield the shortest return route based on the original, but it wouldn't necessarily be the shortest route possible... which is more plausible.