From Swarm Simulations to Swarm Intelligence

In self-organizing systems such as collective intelligent behaviors of animal or insect groups: flocks of birds, colonies of ants, schools of fish, swarms of bees, etc. there are ever emergent patterns which cannot be reduced to a linear composition of elementary subsystems properly. This reduction is possible only due to many repellents and an artificial environment. The emergent patterns are studied in the socalled swarm intelligence. In this paper we show that any swarm can be represented as a conventional automaton such as Kolmogorov-Uspensky machine, but with a very low accuracy because of deleting emergent phenomena. Furthermore, we show as well that implementing some unconventional algorithms of p-adic arithmetic and logic are much more applicable than conventional automata. By using p-adic integers we can code different emergent patterns.