Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

The Data Mining applied for the prediction of highway roughness due to overloaded trucks

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

A autonomia no processo de aquisição da competência plurilingue e intercultural no âmbito da aprendizagem do Espanhol

Relatório de estágio de mestrado em Ensino de Português no 3.º ciclo do Ensino Básico Secundário e do Ensino do Espanhol no Ensino Básico e Secundário

Aprender a gostar de poesia: contributos para uma didática do texto poético em contexto de Educação Pré-Escolar e Ensino do 1º Ciclo

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1º Ciclo do Ensino Básico

Trabalhos para casa no 1.ºCiclo: ter ou não ter, eis a questão

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico

Mais além de quem escreve: “Eu também posso ser Ilustrador”: desenvolvendo múltiplas linguagens num projeto curricular integrado

Relatório de estágio de mestrado em Educação Pré-Escolar

O jogo como potencializador da motivação para a aprendizagem: (des)envolvimento(s) através de um projeto curricular integrado

Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1.º Ciclo do Ensino Básico

Ensino, aprendizagem e avaliação no Ensino Superior: Perspetivas e práticas

Tese de Doutoramento em Ciências da Educação - Especialidade de Desenvolvimento Curricular

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

Viver a (e para) aprender: uma intervenção-ação para a promoção do envelhecimento ativo

A intervenção aqui descrita teve como objetivo contribuir para o envelhecimento ativo de usuários de centros-dia/convívio para idosos, desenvolvendo harmoniosamente todas suas dimensões, visando que os utentes fossem autônomos, participativos e ativos. Recorrendo ao paradigma interpretativo-hermenêutico, apoiamo-nos num trabalho de investigação-ação participativa, construído e implementado em dois centros-dia/convívio do conselho da Póvoa de Lanhoso, distrito de Braga, Portugal, e que contou com um total de 25 usuários: 12 no centro de convívio A e 13 no centro de convívio B. O objetivo foi transversal a todas as atividades implementadas, tendo sido alcançado como revelam os resultados satisfatórios obtidos na avaliação da intervenção (e de cada uma das atividades). A avaliação contínua e final permitiu, igualmente, aferir que todas as atividades desenvolvidas foram do agrado dos usuários e que todas lhes possibilitaram novos conhecimentos que os ajudaram na sua vida diária, aumentando, consequentemente, sua qualidade de vida e tornando-os mais autônomos, participativos e ativos.

Formação continuada de professores para o uso das tecnologias educativas: um estudo de caso sobre o discurso e a prática

Tese de Doutoramento em Ciências da Educação (Especialidade de Tecnologia Educativa)

Foreword [to Digital literacy, technology and social inclusion: making sense of one-to-one computer programmes around the world]

(Excerto) In times past, learning to read, write and do arithmetic was to get on course to earn the “writ of emancipation” in society. These skills are still essential today, but are not enough to live in society. Reading and critically understanding the world we live in, with all its complexity, difficulties and challenges, require not only other skills (learning to search for and validate information, reading with new codes and grammar, etc) but, to a certain extent, also metaskills, matrixes and mechanisms that are transversal to the different and new literacies, are necessary. They are needed not just to interpret but equally to communicate and participate in the little worlds that make up our everyday activities as well as, in a broader sense, in the world of the polis, which today is a global world.

Investigations on relational control of time perception

Tese de Doutoramento em Psicologia Básica

A mudança de hábitos de consumo da classe média em Portugal, no contexto da crise atual

Dissertação de mestrado em Sociologia (área de especialização em Organizações e Trabalho)

Sistema de apoio à aprendizagem na área da discalculia em menores

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Informática Médica)