Social dilemmas occur frequently in human societies. They are situations where there is a conflict between what is good for one individual versus what is good for the group as a whole. Examples include use of private cars rather than public transportation, exploitation of fishing waters, and consumption of electricity. Empricial studies have shown that some groups are able to successfully resolve these dilemmas by creating, monitoring, and enforcing rules about the use of these resources, such that individuals are incentivised to behave in a way that benefits the group as a whole. The studies also show that this tends to work best when groups devise and enforce their own rules, rather than this being done by an external agency such as a centralised government. However, we still lack a clear understanding of the conditions under which groups can successfully create and enforce their own rules to resolve social dilemmas. The project will address this by combining game theory with evolutionary computation to develop models of when groups are likely to be able to devise and enforce their own rules, and when they are not likely to be able to do so. This work could be applied to a range of application areas depending on the interests of the student, including energy production and consumption on smart grids, and the sharing of computational resources on community clouds.