No abstract

The study of multi-criteria problems adapted to the context of Ubiquitous Group Decision Support Systems (UbiGDSS) is covered in the literature through very different perspectives and interests. There are scientific studies related to the multi-criteria problems that lie across argumentation-based negotiation, multi-agent systems, dialogues, etc. However, to perform most of these studies, a high amount of information is required. The usage of so much data or information that is difficult to collect or configure can bring good results in theoretical scenarios but can be impossible to use in the real world. In order to overcome these issues, we present in this paper a general template to configure multi-criteria problems adapted for the contexts of UbiGDSS that intends to be easy and fast to configure, appellative, intuitive, permits to collect a lot of data and helps the decision-maker transmitting his beliefs and opinions to the system. Our proposal includes three sections: Problem Data, Personal Configuration and Problem Configuration. We have developed a prototype with our template with the purpose to simulate the configuration of a multi-criteria problem. We invited real decision-makers to use our prototype in a simulated scenario and asked to them to fulfil a survey in the end in order to study our hypotheses. Our general template achieved good results and proved to be very perceptible and fast to configure.

Supporting group decision-making in ubiquitous contexts is a complex task that must deal with a large amount of factors to succeed. Here we propose an approach for an intelligent negotiation model to support the group decision-making process specially designed for ubiquitous contexts. Our approach can be used by researchers that intend to include arguments, complex algorithms and agents' modelling in a negotiation model. It uses a social networking logic due to the type of communication employed by the agents and it intends to support the ubiquitous group decision-making process in a similar way to the real process, which simultaneously preserves the amount and quality of intelligence generated in face-to-face meetings. We propose a new look into this problematic by considering and defining strategies to deal with important points such as the type of attributes in the multicriteria problems, agents' reasoning and intelligent dialogues.

Supporting and representing the group decision-making process is a complex task that requires very specific aspects. The current existing argumentation models cannot make good use of all the advantages inherent to group decision-making. There is no monitoring of the process or the possibility to provide dynamism to it. These issues can compromise the success of Group Decision Support Systems if those systems are not able to provide freedom and all necessary mechanisms to the decision-maker. We investigate the use of argumentation in a completely new perspective that will allow for a mutual understanding between agents and decision-makers. Besides this, our proposal allows to define an agent not only according to the preferences of the decisionmaker but also according to his interests towards the decision-making process. We show that our definition respects the requirements that are essential for groups to interact without limitations and that can take advantage of those interactions to create valuable knowledge to support more and better.

The market globalization and the firms internationalization hinders the matching of the top managers agenda. Therefore, creating conditions for meetings in the same space or time is sometimes impossible. In order to enable the decision making in this kind of scenario the Group Decision Support Systems evolved to the so called Ubiquitous Group Decision Support Systems (UbiGDSS). However, although the UbiGDSS solve part of space-time problems, they originated other problems related to the lack of human interaction, such as: to understand how the arguments used can influence each of the decision makers, what is their satisfaction regarding the decision made, and other affective issues such as emotions and mood. Here we propose a theoretical model that is specially designed for agents in order to understand the interactions impact on each agent and their satisfaction with the decision made.

Many Multiple Criteria Decision Analysis (MCDA) methods have been proposed over the last decades. Some of the most known methods share some similarities in the way they are used and configured. However, we live in a time of change and nowadays the decision-making process (especially when done in group) is even more demanding and dynamic. In this work, we propose a Multiple Criteria Decision Analysis method that includes cognitive aspects (Cognitive Analytic Process). By taking advantage of aspects such as expertise level, credibility and behaviour style of the decision-makers, we propose a method that relates these aspects with problem configurations (alternatives and criteria preferences) done by each decision-maker. In this work, we evaluated the Cognitive Analytic Process (CAP) in terms of configuration costs and the capability to enhance the quality of the decision. We have used the satisfaction level as a metric to compare our method with other known MCDA methods in literature (Utility function, AHP and TOPSIS). Our method proved to be capable to achieve higher satisfaction levels compared to other MCDA methods, especially when the decision suggested by CAP is different from the one proposed by those methods.

Supporting decision-making processes when the elements of a group are geographically dispersed and on a tight schedule is a complex task. Aiming to support decision-makers anytime and anywhere, Web-based Group Decision Support Systems have been studied. However, the limitations in the decision-makers' interactions associated to this scenario bring new challenges. In this work, we propose a set of behavioral styles from which decision-makers' intentions can be modelled into agents. The goal is that, besides having agents represent typical preferences of the decision-makers (towards alternatives and criteria), they can also represent their intentions. To do so, we conducted a survey with 64 participants in order to find homogeneous operating values so as to numerically define the proposed behavioral styles in four dimensions. In addition, we also propose a communication model that simulates the dialogues made by decision-makers in face-to-face meetings. We developed a prototype to simulate decision scenarios and found that agents are capable of acting according to the decision-makers' intentions and fundamentally benefit from different possible behavioral styles, just as a face-toface meeting benefits from the heterogeneity of its participants.

In future, the organizations' likelihood to endure and succeed will depend greatly on the quality of every decision made. It is known that most decisions in organizations are made in group. With the purpose of supporting decision-makers anytime and anywhere, Web-based Group Decision Support Systems (GDSS) have been studied. The amount of Web-based GDSS incorporating automatic negotiation mechanisms such as argumentation has been steadily increasing. Usually, these systems/models are evaluated through mathematical proofs, number of rounds or seconds to propose (reach) a solution. However, those techniques are not very informative in terms of the decision quality. Here, we propose a model that intends to predict the decision-makers' satisfaction (perception of the decision quality), specifically designed to deal with multi-criteria problems. Our model considers aspects such as: meeting's outcomes, decision-maker's intentions, expectations and emotional cost. To validate the proposed model in terms of its ability to predict decision-makers' satisfaction, we developed a prototype of a Webbased GDSS to be used in a case study where the participant had to make a joint decision. The decision process consisted in a set of 5 rounds, where the participant could (re)configure his/her preferences along the process. The satisfaction model ascertained its ability to predict the participants' satisfaction and allowed to understand that (as is stated in the literature) the inclusion of cognitive and emotional variables is essential to evaluate satisfaction more accurately.