Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

A influência da poesia no desenvolvimento da linguagem oral de uma aluna com Trissomia 21

O conceito de poesia é uma forma de arte e traduz-se como um espelho do pensamento do homem realizado na palavra oral e escrita. A poesia poderá ensinar o homem no estudo da palavra, através do seu significado nos valores denotativo e/ou conotativo. A aplicação destes conceitos faz sentido, a partir da ideia de que a palavra no contexto da poesia pode produzir emoções e sensações nas pessoas a quem ela é transmitida. A poesia tem funções multissensoriais que podem definir o input linguístico como forma de desenvolver a linguagem. Vários são os estudos que apontam para as principais competências deficitárias nos indivíduos com Trissomia 21, mas poucas são as investigações que se debruçam sobre a influência da poesia nas várias competências linguísticas. Uma perceção mais ampla e visionária da Arte na voz da poesia pela parte da escola, professores e, em particular, professores de Educação Especial permitirá adotar estratégias de intervenção inovadoras. Pretende este estudo investigar e analisar a forma como a poesia pode influenciar o desenvolvimento da linguagem oral numa aluna com Trissomia 21. Neste projeto, a partir da identificação do caso-problema e da constatação da ausência da poesia no currículo da aluna, procurou-se intervir, no sentido de melhorar as suas competências linguísticas, utilizando para tanto a poesia. A implementação do projeto aconteceu ao longo de seis meses durante quinze sessões de intervenção individuais. Os resultados do projeto mostram que, em todas as competências linguísticas, houve um processo evolutivo, sendo particularmente significativo o desenvolvimento da competência fonológica, aumento de vocabulário e uma maior noção da palavra em contexto. Estes dados levam-nos a crer que a utilização da poesia poderá, também, constituir uma forma de promover a socialização e a autonomia, revelando os efeitos colaterais que poderão decorrer deste tipo de intervenção. - Abstract The concept of poetry is a form of art, showing the man's thought held in the spoken and written word. Poetry can teach man in the study of the word, its meaning through denotative and/or connotative values. The application of these concepts makes sense, from the idea that the word in the context of poetry can stir emotions and feelings in the people to whom it is transmitted. Poetry has multisensory functions that can set the linguistic input as a way to develop language at phonological, lexical, semantics, pragmatic and morfosyntactic skills. There are several studies that point out to the key skills deficit in individuals with Trisomy 21, but there are few investigations that focus on the influence of poetry in various language skills. A broader perception and vision of poetry as art given by school, and teachers, and, particularly teachers of Special Education will allow a more effective intervention strategies. This study aims to investigate and analyze how poetry can influence the development of oral language in a student with Trisomy 21. In this project, we tried to intervene, improving the language skills of the student, using poetry from the identification case-problem and confirmation of the absence of poetry in her curriculum. The implementation of the project took place throughout six months for fifteen individual intervention sessions. The project results show that, in all language skills, there was a progressive process, being particularly significant the development of the phonological skills, increased vocabulary and a greater sense of the word into context. These data lead us to believe that the use of poetry can also be a way to promote socialization and autonomy, revealing the side effects that may result from this type of intervention.

Virtual power producers market strategies

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.

Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.

Transição e adaptação ao ensino superior artístico

A principal finalidade deste artigo é a de contribuir para a compreensão dos fenómenos de adaptação ao ensino superior artístico vivenciados pelos estudantes e percepcionados pelos professores, e a de reflectir sobre os mecanismos de apoio à adaptação que a instituição de acolhimento pode adoptar. Como instrumentos de recolha de dados, foram distribuídos dois questionários aos estudantes do primeiro ano (questionário de caracterização e o Questionário de Adaptação ao Ensino Superior de Lencastre et al., 2000) e realizadas entrevistas semi‑directivas a quatro professores da Escola Superior de Dança do Instituto Politécnico de Lisboa. Os resultados indicaram que, de uma forma geral, as dificuldades de adaptação ao Ensino Superior diagnosticadas noutros estudos realizados no nosso país, nos domínios académico, bio‑psicológico e sócio‑relacional, são também sentidas pelos estudantes da Escola Superior de Dança. Foram, no entanto, identificadas algumas dimensões particulares ao nível de conhecimentos específicos, tais como a heterogeneidade de formações anteriores dos alunos, o seu baixo nível de preparação física para realizar um curso desta natureza e o seu baixo nível de maturidade artística e expressiva. O grande número (57,5%) de estudantes deslocados da sua área de residência, sujeitos a uma enorme carga horária, revelou também que todos os aspectos relacionados com a dimensão sócio‑relacional assumem uma importância acrescida, e que tanto a instituição Escola Superior de Dança como a sua associação de estudantes podem desempenhar um papel importante para minorar as dificuldades de adaptação social e relacional manifestadas.

Multiagent system for adaptive strategy formulation in electricity markets

Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal.

Complex market integration in MASCEM electricity market simulator

The restructuring that the energy sector has suffered in industrialized countries originated a greater complexity in market players’ interactions, and thus new problems and issues to be addressed. Decision support tools that facilitate the study and understanding of these markets become extremely useful to provide players with competitive advantage. In this context arises MASCEM, a multi-agent system for simulating competitive electricity markets. To provide MASCEM with the capacity to recreate the electricity markets reality in the fullest possible extent, it is essential to make it able to simulate as many market models and player types as possible. This paper presents the development of the Complex Market in MASCEM. This module is fundamental to study competitive electricity markets, as it exhibits different characteristics from the already implemented market types.

Estudo dosimétrico comparativo do Acuros® XB: algoritmo avançado de cálculo de dose com o AAA – Anisotropic Analytical Alghorithm, em tratamentos de radioterapia externa com a técnica de RapidArc™

Mestrado em Radioterapia.

VPP´s multi-level negotiation in smart grids and competitive electricity markets

The increase of distributed generation (DG) has brought about new challenges in electrical networks electricity markets and in DG units operation and management. Several approaches are being developed to manage the emerging potential of DG, such as Virtual Power Players (VPPs), which aggregate DG plants; and Smart Grids, an approach that views generation and associated loads as a subsystem. This paper presents a multi-level negotiation mechanism for Smart Grids optimal operation and negotiation in the electricity markets, considering the advantages of VPPs’ management. The proposed methodology is implemented and tested in MASCEM – a multiagent electricity market simulator, developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations.

IGRT com CBCT: o impacto na precisão em radioterapia

Mestrado em Radiações Aplicadas às Tecnologias da Saúde.

Práticas de inclusão de alunos com perturbação do espectro do autismo no 1º Ciclo

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação, especialidade Educação Especial – Problemas Cognitivos e Multideficiência

O teatro na comunidade de Torres Vedras: as práticas de criação e de fruição em torno do grupo do Grémio Artístico Torreense

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Artística - Especialização em Teatro na Educação

Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

MASCEM: electricity markets simulation with strategic agents

Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

A new approach for multi-agent coalition formation and management in the scope of electricity markets

This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition. In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in.