Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.

Polyglutamine diseases (PolyQ): construction and characterization of yeast models

Dissertação apresentada para a obtenção do Grau de Mestre em Genética Molecular e Biomedicina, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

A framework to operate transformations between distinct models differing in modelling concepts

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Massive shift in the pneumococcal nasopharyngeal flora after the 7-valent conjugate vaccine: epidemiological studies and testing pathogenic potential in animal models

Dissertation presented to obtain the PhD degree in Biology/Molecular Biology by Universidade Nova de Lisboa, Instituto de Tecnologia Química e Biológica

Invited review: Models for the optimization of regional wastewater treatment systems

European Journal of Operational Research, nº 73 (1994)

Models and tools for value systems analysis in collaborative environments

Dissertation to obtain the degree of Doctor in Electrical and Computer Engineering, specialization of Collaborative Networks

Estimation of infection rate in epidemic models with multiple populations

Dissertação para obtenção do Grau de Mestre em Matemática e Aplicações Especialização em Actuariado, Estatística e Investigação Operacional

Critical Velocity obtained using Simplified Models of the Railway Track: Viability and Applicability

Increased demands on the capacity of the railway network gave rise to new issues related to the dynamic response of railway tracks subjected to moving vehicles. Thus, it becomes important to evaluate the applicability of traditionally used simplified models which have a closed form solution. Regarding simplified models, transversal vibrations of a beam on a visco-elastic foundation subjected to a moving load are considered. Governing equations are obtained by Hamilton’s principle. Shear distortion, rotary inertia and effect of axial force are accounted for. The load is introduced as a time varying force moving at a constant velocity. Transversal vibrations induced by the load are solved by the normal-mode analysis. Reflected waves at the extremities of the full beam are avoided by introduction of semi-infinite elements. Firstly, the critical velocity obtained from this model is compared with results of an undamped Euler- Bernoulli formulation with zero axial force. Secondly, a finite element model in ABAQUS is examined. The new contribution lies in the introduction of semi- infinite elements and in the first step to a systematic comparison, which have not been published so fa