The evolution of rules for conflicts resolution in self-organizing teams

The purpose of the paper is to study the emergency and effects of conflict resolution rules in self-organizing teams. Intelligent agents are used to simulate team members of self-organizing teams. In the virtual self-organizing team, agents adapt the Q-learning algorithm to adjust their actions. Three sets of experiments are manipulated to study the evolution of rules. The results of few experiments show a new rule for conflict resolution emerged from the dynamic interactions of agents. For the other experiments, agents cannot resolve conflicts by themselves.

► The emergency of the new rule can be proposed by the multi-agent model.
► The increase of conflicts’ amount at each period blocks the evolution of new rules.
► The increase of team scale can not promote the emergency of new rule for conflict resolution.