Collaboration among computational agents through indirect reciprocity
Master thesis
Permanent lenke
http://hdl.handle.net/11250/2615801Utgivelsesdato
2018Metadata
Vis full innførselSamlinger
Sammendrag
Indirect reciprocity is a mechanism for collaboration from evolutionary theory that attemptsto explain the occurrence of altruism. It explains how a population of entities canmake a decision of whether to cooperate in an interaction on the basis of the reputationof others. This basis of collaboration is largely seen in humans. We possess superiorcommunicative and cognitive abilities compared to other species, enabling us to share andevaluate information through rumors of what happens between other people. There arelimitation in the effectiveness in the indirect reciprocity we see in humans. People onlycollaborate when they have a reason to do so, and will hold back if there is uncertaintyif an act of helping will ever be reciprocated. The lack of trust and uncertainty increaseswith the number of people that partake in such a mechanism, as we have a hard timecommunicating and reasoning about large amounts of information.We identify that uncertainty in the evaluation of other peoples reputation, as well as thecost of maintaining a reputation on an entire population acts as limitations of indirectreciprocity.Representing humans through computational agents allows us to increase the mere sizeof information we are able to communicate and reason about. We provide agents with apublic observation model using blockchain technology and smart contracts, enabling themto have access to information about encounters between the other agents. The agents aregranted with certainty that the information from the observation model is correct. Theysign contracts as proof that interactions occur using asymmetric encryption. The resultingcontracts are used as a basis for the evaluation of reputation of other agents. We use socialnorms to define good behaviour, and consequently how the agents assess the reputationof other agents. Every agent conforms to a social norm of their choice, and as a consequencethey have a subjective opinion on which agents have good reputation. Throughsocial learning by imitating agents that perform better, the population converges to a homogeneousone in terms of social norms. Using a strict discriminating social norm suchas stern-judging, we see a near perfect cooperation rate where the population successfullydiscriminates agents employing other social norms.