Group interactions based on agent opinion

Cooperative behavior among single agents based on interaction history has been a stimulating field of research among social scientists and multi-agent researchers. The situation becomes complex in case of a group of agents seeking help from another group. The opinion of the members of the helping group about each of the asking group members can be combined to evaluate such a request for help. Exploitative agents would want to be part of groups that receive helps from other groups, but will try to avoid having to help other groups. Such agents, revealing false opinion about the reputation of others, can cause unwarranted penalization of the requesting group. This leads to global performance degradation in terms of reduced inter-group cooperation, and increased cost for the individual agents. We assume randomly formed, shortlived group compositions and study two strategies to use the collective opinion of the members of a helping group and identify situations where truthful agents are able to maintain lower costs even in presence of lying agents. We also study the relative merits of the tw.o strategies in generating contracts in presence of lying agents.