Changing climate, changing decisions : understanding climate adaptation decision-making and the way science supports it

Tese de doutoramento, Ciências do Ambiente, Universidade de Lisboa, Faculdade de Ciências, Universidade Nova de Lisboa, 2015

Engaging local communities in neighbourhood regeneration in England: an evaluation of aims, objectives and outcomes

This chapter reviews the different approaches to engaging local communities in neighbourhood regeneration over time and concludes with a discussion of the implications of the Localism Act 2011.

Strategic tensions within the smartphones industry: the case of BlackBerry

This paper reviews some aspects of corporate strategy in a well-known smart phone provider. Two approaches to strategy are analysed: one concerning the industry and the other related to the organization. A general introduction on the smart phones industry is given followed by specific background on BlackBerry. Two perspectives are explored: the first talks about the paradox of compliance and choice within the industry and the second discusses the paradox of control and chaos in BlackBerry. The paper concludes with a brief overview on the company performance from 2006 to 2012 leading to some recommendations.

O Planeamento estratégico nos hospitais portugueses num contexto de austeridade: o caso particular dos Hospitais E.P.E.

Dissertação apresentada para obtenção do grau de Mestre em Contabilidade e Finanças Orientador: Professor Doutor José Freitas Santos

Fatores influenciadores da gestão da qualidade e independência do auditor: um estudo de caso

Dissertação apresentada ao Instituto Superior de Contabilidade para obtenção do Grau de Mestre em Auditoria Orientada por: Doutora Alcina Dias

Intelligent decision making in electricity markets: simulated annealing Q-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 is integrated with ALBidS, a system that provides several dynamic strategies for agents’ behavior. This paper presents a method that aims at enhancing ALBidS competence in endowing market players with adequate 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 actions. These actions are defined accordingly to the most probable points of bidding success. With the purpose of accelerating the convergence process, a simulated annealing based algorithm is included.

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.

Plano de marketing para a empresa: Salss - Importação e Comércio Lda

Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

Campanha de comunicação de Ambient Media para a marca Leroy Merlin

Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.