Diogo Martinho

Intelligent negotiation model for ubiquitous group decision scenarios

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 specifically designed for ubiquitous contexts. Our approach can be used by researchers that intend to include arguments, complex algorithms, and agents’ modeling 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 problem by considering and defining strategies to deal with important points such as the type of attributes in the multicriterion problems, agents’ reasoning, and intelligent dialogues.

Dealing with agents’ behaviour in the decision-making process

This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124- FEDER-028980 (PTDC/EEISII/1386/2012) and SFRH/BD/89697/2012.

Defining Agents’ Behaviour for Negotiation Contexts

Agents who represent participants in the group decision-making context require a certain number of individual traits in order to be successful. By using argumentation models, agents are capable to defend the interests of those who they represent, and also justify and support their ideas and actions. However, regardless of how much knowledge they might hold, it is essential to define their behaviour. In this paper (1) is presented a study about the most important models to infer different types of behaviours that can be adapted and used in this context, (2) are proposed rules that must be followed to affect positively the system when defining behaviours and (3) is proposed the adaptation of a conflict management model to the context of Group Decision Support Systems. We propose one approach that (a) intends to reflect a natural way of human behaviour in the agents, (b) provides an easier way to reach an agreement between all parties involved and (c) does not have high configuration costs to the participants. Our approach will offer a simple yet perceptible configuration tool that can be used by the participants and contribute to more intelligent communications between agents and makes possible for the participants to have a better understanding of the types of interactions experienced by the agents belonging to the system.

Dynamic argumentation in UbiGDSS

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 decision-maker 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.

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

Abstract 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-to-face meeting benefits from the heterogeneity of its participants.

Including Credibility and Expertise in Group Decision-Making Process: An Approach Designed for UbiGDSS

Supporting group decision-making when the decision-makers are spread around the world is a complex process. The mechanisms of automated negotiation, such as argumentation, can be used in Ubiquitous Group Decision Support Systems to help decision-makers find a solution based on their preferences. However, there are some other important issues that affect the decision-making process beyond typical preferences over criteria and alternatives. In this paper, we propose an algorithm that will allow agents to reason about self-expertise and other decision makers’ credibility. This way, we intend agents to achieve better quality and more consensual decisions. Our algorithm includes not only the decision-maker’s preferences but also his intentions in the process. By using the proposed model, agents achieved a stronger consensus in all scenarios that were considered and higher satisfaction levels in the most complex scenarios.

The Effect of Decision Satisfaction Prediction in Argumentation-Based Negotiation

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.

Generation of intelligent reports for ubiquitous group decision support systems

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 agents representing decision-makers are not able to understand the process and support them accordingly. In this work we present some topics of information that can be reported to decision-makers to improve their perception about the negotiation process. We classified those topics according to two dimensions and we defined an algorithm to select which information will be built for each report.

Introducing Dynamic Argumentation to UbiGDSS

Supporting and representing the group decision-making process is a complex task that requires very specific characteristics. 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 decision-maker 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.

Intelligent reports for group decision support systems

This work has been supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT - Portuguese Foundation for Science and Technology within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, and the Joao Carneiro PhD grant with the reference SFRH/BD/89697/2012.