Abstract
The continuous changes in electricity markets' mechanisms and operations turn this environment into a challenging domain for the participating entities. Simulation tools are increasingly being used for decision support purposes of such entities. In particular, multi-agent based simulation, which facilitates the modeling of different types of mechanisms and players, is being fruitfully applied to the study of worldwide electricity markets. An effective decision support to market players' negotiations is, however, still not properly reached due to the uncertainty that results from the increasing penetration of renewable generation and the complexity of market mechanisms themselves. In this scope, this paper proposes a novel metalearner that provides decision support to market players in their negotiations. The proposed metalearner uses as input the output of several other market negotiation strategies, which are used to create a new, enhanced response. The final result is achieved through the combination and evolution of the strategies' learning results by applying a genetic algorithm.

Abstract
Este capítulo proporciona uma narrativa e reflexão sobre as dinâmicas de aprendizagem e contacto com o espaço físico no âmbito de um ano de participação do autor no jogo Ingress, da Google. Como jogo georreferenciado de realidade alternativa, recorre ao espaço físico que nos rodeia, mas reinterpretado com camadas de informação digital. Como jogo mundial de milhares de utilizadores simultâneos, reunidos em apenas duas equipas mundiais, requer coordenação de esforços, estratégias e colaboração. Como jogo que combina ficção científica com mistério, baseado numa narrativa incompleta que vai sendo revelada, combina dados implícitos, explícitos e ocultos, requerendo cruzamento de informações e perspetivas entre jogadores. Como jogo que é desenvolvido tecnicamente ao longo deste período, com alterações constantes de regras e funcionalidades, requer adaptação rápida às consequências e dinâmicas sociais. Pretende-se com esta narrativa e reflexão descortinar o potencial deste tipo de jogos para dinâmicas e atividades de aprendizagem formal ou informal.

Abstract
Apresentamos um conceito de jogo inovador e o seu protótipo inicial, integrando tipos distintos de interação e de visualização. Dois jogadores interagem como timoneiro de uma nau portuguesa e gigante Adamastor. Um joga em realidade virtual controlada por gestos finos, outro usa aumentação contextual com gestos amplos e fi-nos. Pretende o conceito e o protótipo servirem como exemplificadores das potencialidades das novas formas de interação e de como as concretizar.

Abstract
Stress is a highly complex, subjective and multidimensional phenomenon. Nonetheless, it is also one of our strongest driving forces, pushing us forward and preparing our body and mind to tackle the daily challenges, independently of their nature. The duality of the effects of stress, that can have positive or negative effects, calls for approaches that can take the best out of this biological mechanism, providing means for people to cope effectively with stress. In this paper we propose an approach, based on mouse dynamics, to assess the level of stress of students during online exams. Results show that mouse dynamics change in a consistent manner as stress settles in, allowing for its estimation from the analysis of the mouse usage. This approach will allow to understand how each individual student is affected by stress, providing additional valuable information for educational institutions to efficiently adapt and improve their teaching processes.

Abstract
The recent interest in smart grid vision enables several smart applications in different parts of the power grid structure, where specific importance should be given to the demand side. As a result, changes in load patterns due to demand response (DR) activities at end-user premises, such as smart households, constitute a vital point to take into account both in system planning and operation phases. In this study, the assessment of the impacts of pricing based DR strategies on smart household load pattern variations is provided. The household load data sets are acquired from a provided model of a smart household, including appliance scheduling. Then, an artificial neural network (ANN) approach based on Wavelet Transform (WT) is employed for the forecasting of responsive residential load behaviors to different pricing schemes. From the literature perspective this study contributes by considering DR impacts on load pattern forecasting, being a very useful tool for market participants such as aggregators in future pool-based market structures, or for load serving entities to discuss potential change requirements in existing DR strategies, or even to effectively plan new ones.

Abstract