  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.
