Conflicts in Information Ecosystems

Abstract: The main topic of this thesis concerns the study of how conflicting interests of software agents within an information ecosystem may cause cooperative behavior. Since such agents act on the behalf of their human owners, which often act in their own interest, this will sometimes result in malignant acts. Different types of models, often inspired by biological theories such as natural selection, will be used to describe various aspects of such information ecosystems. We begin by adopting a game theoretic approach where a generous and greedy model is introduced. Different agent strategies for iterated games are compared and their ability to cooperate in conflicting games are evaluated in simulation experiments. The conclusion is that games like the chicken game favor more complex and generous strategies whereas in games like the prisoner’s dilemma, the non-generous strategy tit-for-tat often is the most successful. We then use models based on a surplus value concept to explain antagonistic group formations. The focus is on systems that consist of exploiter agents and agents being exploited. A dynamic protection model of access control is proposed, where a chain of attacks and countermeasures concerning the access are measured. This process can be described as an arms race. It is argued that arms race is a major force in the interaction between antagonistic agents within information ecosystems. Examples of this are given in several contexts such as peer-to-peer tools concerning anonymity and non-censorship, using agents for sending or filtering out mass distributed advertisement e-mails, and finally for describing the fight against viruses or spywares.