Generation and evaluation of different types of arguments in negotiation

Until now, AI argumentation-based systems have been mainly developed for handling inconsistency. In that explanation-oriented perspective, only one type of argument has been considered. Several argumentation frameworks have then been proposed for generating and evaluating such arguments. However, recent works on argumentation-based negotiation have emphasized different other types of arguments such as threats, rewards, appeals, etc... The purpose of this paper is to provide a logical framework which encompass the classical argumentation-based framework and handles the new types of arguments. More precisely, we give the logical definitions of these arguments and their weighting systems. These definitions take into account that negotiation dialogues involve not only agents’ beliefs (of various strengths) but also their goals (having maybe different priorities), the beliefs on the goals of other agents, etc... In other words, from the different belief and goal bases maintained by an agent, we can generate all the possible threats, rewards, explanations, appeals which are associated to them. Finally, we show how to evaluate conflicting arguments of different types. The possibilistic logic framework is used for handling formulas with different degrees of certainty or priority.