Abstract
E-Learning, much like any other communication processes, has been significantly shaped by technological evolution. In its original form, e-Learning aimed to bring the education closer to people, making it more modular and personalized. However, in reality, we observe that it represents a separation between student and teacher, simplifying this relationship to the exchange of "text-based messages", leaving aside all the important contextual richness of the classroom. We are addressing this issue by devising a contextual layer for e-Learning platforms. Particularly, in this paper we describe a solution to convey information about the level of stress of the students so that the teacher can take better and more informed decisions concerning the management of the learning process.

Abstract
In our living, we often have a sense of being tired due to a mental or physical work, plus a feeling of performance degradation even in the accomplishment of simple tasks. However, these mental states are often not consciously felt or are ignored, an attitude that may result in human failures, errors and even in the occurrence of health problems or on a decrease in the quality of life. States of fatigue may be detected with a close monitoring of some indicators, such as productivity, performance or even the health states. In this work it is proposed a model and a prototype to detect and monitor fatigue based on some of these items. We focus specifically on mental fatigue, a key factor in an individual's performance. With this approach we aim to develop leisure and work context-aware environments that may improve the quality of life and the individual performance of any human being.

Abstract
The process of devising solutions for conflict resolution generally configures a challenging task. There exist different approaches to address the problem, namely the use of case-based models or even relying on the parties themselves to perform the task. From a computational point of view, these problems generally represent a NP-complete problem. In order to surpass this shortcoming, in this paper it is presented a biologically inspired method to deal with the problem in which genetic algorithms are used to create possible solutions for a given dispute. The approach presented is able to generate a broad number of diverse solutions that cover virtually the whole search space for a given problem. This approach provides better results than a case-based approach since: (1) it is independent of the legal domain and (2) it does not depend on the number and quality of cases present in a database. The results of this work are being applied in a negotiation tool that is part of the UMCourt conflict resolution platform.

Abstract
The growing use of Information Technology in the commercial arena leads to an urgent need to find alternatives to traditional dispute resolution. New tools from fields such as artificial intelligence (AI) should be considered in the process of developing novel online dispute resolution (ODR) platforms, in order to make the ligation process simpler, faster and conform with the new virtual environments. In this work, we describe UMCourt, a project built around two sub-fields of AI research: Multi-agent Systems and Case-Based Reasoning, aimed at fostering the development of tools for ODR. This is then used to accomplish several objectives, from suggesting solutions to new disputes based on the observation of past similar disputes, to the improvement of the negotiation and mediation processes that may follow. The main objective of this work is to develop autonomous tools that can increase the effectiveness of the dispute resolution processes, namely by increasing the amount of meaningful information that is available for the parties.

Abstract
In our daily living, the environment surrounding us influences us as much or more than we influence it. Whether it is a domestic, leisure or working environment, its conditions will certainly have short and long-term effects on aspects such as stress, mood or fatigue, which will in turn influence indicators such as productivity, quality of work, quality of life, personal/group performance or even health. In this paper a dynamic environment is proposed that, based on the behavioural analysis of its users, will adapt its conditions to improve particular indicators. This will result in better working environments, with an impact on the quality of the work produced. © Springer International Publishing Switzerland 2013.

Abstract
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. © Springer-Verlag Berlin Heidelberg 2013.