The Effect of Decision Satisfaction Prediction in Argumentation-Based Negotiation

Abstract

Abstract. Supporting group decision-making is a complex process, especially when decision-makers have no opportunity to gather at the same place and at the same time. Besides that, finding solutions may be difficult in case representing agents are not able to understand the process and support the decision-maker accordingly. Here we propose a model and an algorithm that will allow the agent to analyse tendencies. This way we intend that agents can achieve decisions with more quality and with higher levels of consensus. Our model allows the agent to redefine his objectives to maximize both his and group satisfaction. Our model proved that agents that use it will obtain higher average levels of consensus and satisfaction. Besides that, agents using this model will obtain those higher levels of consensus and satisfaction in most of the times compared to agents that do not use it.

Representing decision-makers using styles of behavior: An approach designed for group decision support systems

“…We have created several simulation environments because we considered at the outset that because agents act using different behavioral styles, their behavior may vary according to the number of agents and the behavioral style of the other agents with which they are involved in the decision process. We used the multicriteria problem previously used in case studies as presented in Carneiro, Martinho, Conceição, Marreiros, and Novais (2017); Carneiro, Martinho, Marreiros, and Novais (2016a) and each agent generated its preferences regarding the alternatives and criteria in a "random" way. Initially each agent randomly generated its preferences regarding the criteria and then, based on these preferences, it generated the preferences of the alternatives with a randomness that made would be plausible taking into account the values of the criteria of each alternative and preferences of previously generated criteria.…”