Simulation of Ant Colony Optimization (ACO) and Swarm Intelligence. In this case, both aspects of functioning ant colony, i.e., food transport as well as food search are equally prioritized. Ants movements are governed by changing its acceleration in the direction of constantly changing target, computing its velocity and finally adding velocity vector it its position. This is the trivial part. The most difficult part is computing a target position for a given ant. Should the ant go and help transport the food? or should it go and help find food? Believe it or not, there is no centralized authority in an ant colony. Ants make decisions based on several environmental factors and what other worker ants are doing in the vicinity. The emergence of intelligence in an ant colony is solely based on the localized rules of an ants behavior. In fact, Ants dont have a unified view or map of their colony and nor do they know anything beyond their immediate vicinity. They dont have memory. Their pheromone trails only mark the path for a short period of time before it evaporates. Collectively and amazingly, they do intelligent things such as transporting food, storage, defense, search, etc. Just goes to show how tremendously complex, fascinating and beautiful nature is. Further reading: https://en.wikipedia.org/wiki/Swarm_intelligence amazon/Swarm-Intelligence-Artificial-Institute-Complexity/dp/0195131592 amazon/The-Sciences-Artificial-3rd-Edition/dp/0262691914
Posted on: Sun, 28 Sep 2014 20:24:37 +0000
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