As automated negotiating agents become more and more part of our daily life, additional care needs to be taken that the agents can negotiate fairly. Humans each have their own intrinsic view on fairness, which affects the negotiation processes and the degree to which the outcome is viewed as satisfactory. However, most current agents are built around a specific notion of fairness, which could be potentially unwanted in certain scenarios or by some individuals. This paper presents a generic framework through which varying fairness notions can be implemented. The performance of the framework is tested through a selection of proposed agents with different fairness views. The results show that the agents are able to reach an agreement on the pareto frontier that is fair given their notion. Thus they do not sacrifice optimality for fairness.