Agent Inferencing Meets the Semantic Web

We provide all agent; the capability to infer the relations (assertions) entailed by the rules that, describe the formal semantics of art RDFS knowledge-base. The proposed inferencing process formulates each semantic restriction as a rule implemented within a, SPARQL query statement. The process expands the original RDF graph into a fuller graph that. explicitly captures the rule's described semantics. The approach is currently being explored in order to support descriptions that follow the generic Semantic Web Rule Language. An experiment, using the Fire-Brigade domain, a small-scale knowledge-base, is adopted to illustrate the agent modeling method and the inferencing process.

Multi-agent management system for electric vehicle charging

This paper proposes an implementation, based on a multi-agent system, of a management system for automated negotiation of electricity allocation for charging electric vehicles (EVs) and simulates its performance. The widespread existence of charging infrastructures capable of autonomous operation is recognised as a major driver towards the mass adoption of EVs by mobility consumers. Eventually, conflicting requirements from both power grid and EV owners require automated middleman aggregator agents to intermediate all operations, for example, bidding and negotiation, between these parts. Multi-agent systems are designed to provide distributed, modular, coordinated and collaborative management systems; therefore, they seem suitable to address the management of such complex charging infrastructures. Our solution consists in the implementation of virtual agents to be integrated into the management software of a charging infrastructure. We start by modelling the multi-agent architecture using a federated, hierarchical layers setup and as well as the agents' behaviours and interactions. Each of these layers comprises several components, for example, data bases, decision-making and auction mechanisms. The implementation of multi-agent platform and auctions rules, and of models for battery dynamics, is also addressed. Four scenarios were predefined to assess the management system performance under real usage conditions, considering different types of profiles for EVs owners', different infrastructure configurations and usage and different loads on the utility grid (where real data from the concession holder of the Portuguese electricity transmission grid is used). Simulations carried with the four scenarios validate the performance of the modelled system while complying with all the requirements. Although all of these have been performed for one charging station alone, a multi-agent design may in the future be used for the higher level problem of distributing energy among charging stations. Copyright (c) 2014 John Wiley & Sons, Ltd.

Learning and Knowledge in the Context of Absorptive Capacity

Develop a new model of Absorptive Capacity taking into account two variables namely Learning and knowledge to explain how companies transform information into knowledge

Web 2.0 and its impact on knowledge and business organizations

Today, information overload and the lack of systems that enable locating employees with the right knowledge or skills are common challenges that large organisations face. This makes knowledge workers to re-invent the wheel and have problems to retrieve information from both internal and external resources. In addition, information is dynamically changing and ownership of data is moving from corporations to the individuals. However, there is a set of web based tools that may cause a major progress in the way people collaborate and share their knowledge. This article aims to analyse the impact of ‘Web 2.0’ on organisational knowledge strategies. A comprehensive literature review was done to present the academic background followed by a review of current ‘Web 2.0’ technologies and assessment of their strengths and weaknesses. As the framework of this study is oriented to business applications, the characteristics of the involved segments and tools were reviewed from an organisational point of view. Moreover, the ‘Enterprise 2.0’ paradigm does not only imply tools but also changes the way people collaborate, the way the work is done (processes) and finally impacts on other technologies. Finally, gaps in the literature in this area are outlined.

A hybrid approach to multi-agent decision-making

In the aftermath of a large-scale disaster, agents' decisions derive from self-interested (e.g. survival), common-good (e.g. victims' rescue) and teamwork (e.g. fire extinction) motivations. However, current decision-theoretic models are either purely individual or purely collective and find it difficult to deal with motivational attitudes; on the other hand, mental-state based models find it difficult to deal with uncertainty. We propose a hybrid, CvI-JI, approach that combines: i) collective 'versus' individual (CvI) decisions, founded on the Markov decision process (MDP) quantitative evaluation of joint-actions, and ii)joint-intentions (JI) formulation of teamwork, founded on the belief-desire-intention (BDI) architecture of general mental-state based reasoning. The CvI-JI evaluation explores the performance's improvement

RFID together with multi-agent systems to control global value chains

Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.

Symbolic Knowledge Extraction from Trained Neural Networks Governed by Lukasiewicz Logics

This work describes a methodology to extract symbolic rules from trained neural networks. In our approach, patterns on the network are codified using formulas on a Lukasiewicz logic. For this we take advantage of the fact that every connective in this multi-valued logic can be evaluated by a neuron in an artificial network having, by activation function the identity truncated to zero and one. This fact simplifies symbolic rule extraction and allows the easy injection of formulas into a network architecture. We trained this type of neural network using a back-propagation algorithm based on Levenderg-Marquardt algorithm, where in each learning iteration, we restricted the knowledge dissemination in the network structure. This makes the descriptive power of produced neural networks similar to the descriptive power of Lukasiewicz logic language, minimizing the information loss on the translation between connectionist and symbolic structures. To avoid redundance on the generated network, the method simplifies them in a pruning phase, using the "Optimal Brain Surgeon" algorithm. We tested this method on the task of finding the formula used on the generation of a given truth table. For real data tests, we selected the Mushrooms data set, available on the UCI Machine Learning Repository.

Territórios educativos de intervenção prioritária: de onde vêm? para onde vão?

A criação da medida de política educativa (Despacho Normativo n.º 55/2008) - Territórios Educativos de Intervenção Prioritária (TEIP) corresponde à necessidade de concretização de um princípio da Lei de Bases do Sistema Educativo português, visando assegurar uma educação de base para todos, bem sucedida. Esta mesma medida acontece na sequência de uma outra anterior com as mesmas características, criada no ano lectivo de 1996/1997. A sua implementação no terreno foi objecto de um estudo encomendado pelo Instituto de Inovação Educacional no qual participei, integrando uma equipa de investigação da Faculdade de Psicologia e Ciências da Educação da Universidade de Lisboa. Nesta comunicação, proponho-me revisitar esse mesmo estudo, dando conta do balanço crítico então realizado, e, à luz das suas principais conclusões, refletir agora na qualidade de perito externo de um TEIP da região de Lisboa, sobre os modos como os TEIP2 evoluíram, em que sentido se deu tal evolução e quais os problemas que persistem. A consecução de um dos objectivos centrais desta medida de política educativa, especificamente a melhoria da qualidade das aprendizagens traduzida no sucesso educativo dos alunos, parece, de acordo com os relatórios oficiais, não ser ainda muito expressiva nem muito consistente. Torna-se, portanto, necessário interrogar e problematizar as práticas de ensino realizadas pelos professores, repensando estratégias pedagógicas que se configurem relevantes para dar expressão real àquele objectivo.

Agentes comerciais: modelos de avaliação de risco e rentabilidade

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica na Área de Especialização de Energia

Avaliação comparativa dos efeitos da introdução dos eurocódigos no cálculo sísmico de edifícios de betão armado

Dissertação de natureza Científica para obtenção do grau de Mestre na Área de Especialização de Estruturas

Prática de ensino supervisionado no 1.º e 2.º ciclo do ensino básico: esquemas organizadores facilitadores da aprendizagem em História e Geografia

Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino de 1.º e 2.º Ciclos do Ensino Básico

Prática baseada na evidência em terapia da fala

Mestrado em Gestão e Avaliação em Tecnologias da Saúde

Propriedades de investimento : A problemática das diferentes bases de mensuração no contexto dos grupos económicos. O caso particular da Sonae Sierra

Mestrado em Contabilidade

Relatório de estágio na Empresa Biodroid Entertainment

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Redes de Comunicação e Multimédia

Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff. © 2014 IEEE.