Marco Gomes

Developing dynamic conflict resolution models based on the interpretation of personal conflict styles

Conflict resolution is a classic field of Social Science research. However, with conflicts now also emerging in virtual environments, a new field of research has been developing in which Artificial Intelligence and particularly Ambient Intelligence are interesting. As result, the field of Online Dispute Resolution emerged as the use (in part or entirely) of technological tools to solve disputes. In this paper we focus on developing conflict resolution models that are able to adapt strategies in real time according to changes in the personal conflict styles of the parties. To do it we follow a novel approach in which an intelligent environment supports the lifecycle of the conflict resolution model with the provision of important context knowledge. The presented framework is able to react to important changes in the context of interaction, resulting in a conflict resolution approach that is able to perceive the parties and consequently achieve better outcomes.

STUDYING THE EFFECTS OF STRESS ON NEGOTIATION BEHAVIOR

Negotiation is a collaborative activity that requires the participation of different parties whose behaviors influence the outcome of the whole process. The work presented here focuses on the identification of such behaviors and their impact on the negotiation process. The premise for this study is that identifying and cataloging the behavior of parties during a negotiation may help to clarify the role that stress plays in the process. To do so, an experiment based on a negotiation game was implemented. During this experiment, behavioral and contextual information about participants was acquired. The data from this negotiation game were analyzed in order to identify the conflict styles used by each party and to extract behavioral patterns from the interactions, useful for the development of plans and suggestions for the associated participants. The work highlights the importance of the knowledge about social interactions as a basis for informed decision support in situations of conflict.

Automatic classification of personal conflict styles in conflict resolution

Carneiro D., Gomes M., Novais P., Andrade F., Neves J. Automatic Classification of Personal Conflict Styles in Conflict Resolution. In Legal Knowledge and Information Systems - JURIX 2011: The Twenty-Fourth Annual Conference, Katie M. Atkinson (Ed), IOS Press - Frontiers in Artificial Intelligence and Applications, Vol. 235, ISBN 978-1-60750-980-6, pp 43-52, 2011.

Non-invasive estimation of stress in conflict resolution environments

The current trend in Online Dispute Resolution focuses mostly on the development of technological tools that allow parties to solve conflicts through telecommunication means. However, this tendency leaves aside key issues, namely our concern with respect to context information that was previously available in traditional Alternative Dispute Resolution processes. The main weakness of this approach is that conflict resolution may become a cold process, focused solely on objective questions. In order to overcome this inconvenience, we move forward to incorporate context information in an Online Dispute Resolution platform. In particular, we consider the estimation of the level of stress of the users by analyzing their interaction patterns. As a result, the conflict resolution platform or the mediator may weight to what extent a party is affected by a particular matter, allowing one to adapt the conflict resolution strategy to a specific problem in real time.

A statistical classifier for assessing the level of stress from the analysis of interaction patterns in a touch screen

This paper describes an approach for assessing the level of stress of users of mobile devices with tactile screens by analysing their touch patterns. Two features are extracted from touches: duration and intensity. These features allow to analyse the intensity curve of each touch. We use decision trees (J48) and support vector machines (SMO) to train a stress detection classifier using additional data collected in previous experiments. This data includes the amount of movement, acceleration on the device, cognitive performance, among others. In previous work we have shown the co-relation between these parameters and stress. Both algorithms show around 80% of correctly classified instances. The decision tree can be used to classify, in real time, the touches of the users, serving as an input to the assessment of the stress level.

Modelling stress recognition in conflict resolution scenarios

The current trend in Online Dispute Resolution focuses mostly on the development of technological tools that allow parties to solve conflicts through telecommunication means. However, this tendency leaves aside key issues, namely the context information that was previously available in traditional Alternative Dispute Resolution processes. The main weakness of this approach is that conflict resolution may become focused solely on objective issues. In order to overcome this inconvenience, we move forward to incorporate context and behavioural information in an Online Dispute Resolution platform. In particular, we consider the estimation of the level of stress and the prediction of the stress state evolution. As a result, the conflict resolution platform or the mediator may predict to what extent a party is affected by a particular matter, allowing one to adapt the conflict resolution strategy to a specific scenario in real time.

Improving Modularity, Interoperability and Extensibility in Ambient Intelligence

Ambient Intelligence (AmI) and its related fields emerged some years ago with the exciting promise of pervasive intelligence, magic interaction mechanisms, and everywhere availability. This promise would be materialized in homes that knew all about our habits and preferences, proactive workplaces to support people’s work or personal digital assistants to improve our daily living in all aspects possible. This somewhat utopian vision, expected by many to have already taken place, remains unaccomplished and far from it. Many challenges still lay ahead which delayed and continue to delay the expected technological unravelling. In this paper we focus on the immense technological challenges of designing and implementing AmI Systems. Specifically, we propose a technological approach that will contribute to overcome some of these challenges by making developed AmI solutions more modular, interoperable, and extensible. This will result especially advantageous for large development teams or teams that span multiple institutions.

Extracting Behavioural Patterns from a Negotiation Game

The work presented focuses not only on the behavioural patterns that influence the outcome of a negotiation, but also on the discovery of ways to predict the type of conflict used in the process and the stress levels of the actors. After setting up an experimental intelligent environment provided with sensors to capture behavioural and contextual information, a set of relevant data was collected and analysed, with the underlying objective of using the behavioural patterns (obtained by statistical/probabilistic methods) as a basis to design and present plans and suggestions to the associated participants. In sooth, these proposals may influence in a positive way the course and outcome of a negotiation task in many aspects. This work highlights the importance of knowledge in negotiation, as in other social forms of interaction, providing also some new insights for informed decision support in situations in which uncertainty and conflict may be present.

A Non-intrusive Approach to Measuring Trust in Opponents in a Negotiation Scenario

There is a consensus that trust in one’ opponent plays a significant role in promoting parties to engage in the conflict management process. Trust is an important yet complex and little-understood relation among parties in conflict. In general, trust can be seen as a measure of confidence that an entity or entities will behave expectedly. Without trust, the instruments to prevent or manage the conflict, such as negotiation, are handicapped and cannot reach their full potential for promoting an end to or a mitigation of a conflict. Hence, our motivation to examine trust is three-fold. First, the present study aims to address and expand on this line of research by investigating the possibility of measuring trust based on quantifiable behavior. To do so, we provide a brief review of the existing definitions of trust and define trust in the context of a negotiation scenario. Further, we propose a formal definition so that the analysis of trust in this kind of scenarios can be developed. Thus, it is suggested the use of Ambient Intelligence techniques that use a trust data model to collect and evaluate relevant information based on the assumption that observable trust between two entities (parties) results in certain typical behaviors. Third, this work aims to study the particular connection between relational aspects of trust and parties’ conflict styles based on two dimensions: cooperativeness and assertiveness. The main contribution of this work is the identification of situations in which trust relationships influences the negotiation performance. To do so, an experiment was set-up in which we tried to streamline all the relevant aspects of the interaction between the parties and its environment that occur in a sensory rich environment, to measure trust. To simulate a conflict situation, a web-based game was developed. It was designed to enable test participants to engage in a conflict experience induced by the presence of Ambient Intelligence systems. Several tests were performed. We then engaged in rigorous assessment, post- processing and analysis of results. We validated the results comparing them with trust measures obtained through the use of a questionnaire (carefully adapted) from social networks.

Collaborative Process Mapping to Improve Work Instructions and Standardized Work

Nowadays, companies are searching for models that are able to increase their performance, efficiency and competitiveness. Therefore, it is crucial to identify the current company status and its needs, adopting a suitable model for this. Many times, the success key consists in the adoption of tailor-made models developed by each organization. The company under study has developed a process mapping tool, called Value Stream Design in Indirect Areas (VSDiA) that has been used to map and improve its business processes, in this case, applied to Work Instructions and Standard Work creation. The adoption of this model has allowed the identification of weaknesses, strengths and improvement opportunities in the abovementioned processes, through a collaborative process team work. Furthermore, this tool has provided an overview about the whole process by all involved, as well as, increased transparency and accuracy of the current process and a vision for the future process.