  Traditional evolutionary game theory describes how certain strategy spreads
throughout the system where individual player imitates the most successful
strategy among its neighborhood. Accordingly, player doesn't have own authority
to change their state. However in the human society, peoples do not just follow
strategies of other people, they choose their own strategy. In order to see the
decision of each agent in timely basis and differentiate between network
structures, we conducted multi-agent based modeling and simulation. In this
paper, agent can decide its own strategy by payoff comparison and we name this
agent as "Self-motivated agent". To explain the behavior of self-motivated
agent, prisoner's dilemma game with cooperator, defector, loner and punisher
are considered as an illustrative example. We performed simulation by
differentiating participation rate, mutation rate and the degree of network,
and found the special coexisting conditions.
