
Research Article
From Swarm Simulations to Swarm Intelligence
@INPROCEEDINGS{10.4108/eai.3-12-2015.2262484, author={Andrew Schumann}, title={From Swarm Simulations to Swarm Intelligence}, proceedings={9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)}, publisher={ACM}, proceedings_a={BICT}, year={2016}, month={5}, keywords={swarm intelligence kolmogorov-uspensky machine p-adic valued logic}, doi={10.4108/eai.3-12-2015.2262484} }
- Andrew Schumann
Year: 2016
From Swarm Simulations to Swarm Intelligence
BICT
EAI
DOI: 10.4108/eai.3-12-2015.2262484
Abstract
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 so-called 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.