In traditional policy generation models, the preferences over polices are often represented by qualitative orderings due to the difficulty of acquisition of accurate utility. Thus, it is difficult to evaluate agreements in such models so that players cannot adjust their strategies during a policy generation process. To this end, this paper introduces a negotiation-based model for policy generation, which contains two evaluation methods, both from the perspectives of concessional utilities and consistency, to guide players to make decisions flexibly. The first method is used to model humans¿ reasoning about how to calculate concessional utilities from uncertain preference information of policies based on fuzzy reasoning, while the second method is used to measure similarity between an ideal agreement and an offer based on a prioritised consistency degree. The experimental results show the difference between the evaluation methods and confirm that the proposed model and evaluation methods can help players achieve better agreements than an existing model.