The Role Of Power And Jealousy In Cooperation - A Framework For Artificial Agents

We are interested in the question of how to motivate people to share valuable information so that group performance can be leveraged. In particular, we investigate the impact of power and jealousy on cooperation. It is an unresolved issue how these two social phenomena influence cooperation. We study the impact of power and jealousy to cooperation models by using dynamic artificial agents and agent populations following combined characteristics. We simulate dynamic multi player goods games and we use the Business Transaction Theory as a basic layer for information valuation. Payoff matrices as they are used in evolutionary game theory are also applied. Our motivation to use artificial agents is manifold. First, we are able to simulate small to huge populations in short time, second we are flexible in changing agent characteristics, and third it is hard to find people who admit being jealous in real life. The technical framework is based on the eclipse development environment. The artificial agents are programmed in Java. Our interdisciplinary approach is new since emotions, in context with collaboration, have never been investigated by artificial agents and game theoretical means. Our findings show that incentives might have a big influence on jealousy and even on egoists.