Emergence of Specialization from Global Optimizing Evolution in a Multi-Agent System
Adaptation and Self-Organizing Systems
2007-05-23 v1
Abstract
The evolution of specialization in a multi-agent system is studied both by computer simulation and Markov process model. Many individual agents search for and exploit resources to get global optimization in an environment without complete information. With the selection acting on agent specialization at the level of system and under the condition of increasing returns, the division of labor emerges as the results of long-term optimizing evolution. Mathematical analysis gives the optimum division of agents and a Markov chain model is proposed to describe the evolutionary dynamics. The results are in good agreement with that of simulation model.
Keywords
Cite
@article{arxiv.nlin/0407005,
title = {Emergence of Specialization from Global Optimizing Evolution in a Multi-Agent System},
author = {Zengru Di and Jiawei Chen and Yougui Wang and Zhangang Han},
journal= {arXiv preprint arXiv:nlin/0407005},
year = {2007}
}
Comments
26 pages, 9 Figures