http://hdl.handle.net/10366/139092 2026-04-26T12:00:17Z http://hdl.handle.net/10366/139221 2018-06-29T00:00:00Z http://hdl.handle.net/10366/139220 One important issue in multi-agent systems is how to define agents’ interaction strategies in dynamic open environments. Generally, agents’ behaviors, such as being cooperative/altruistic or competitive/adversarial, are defined a priori by their creators. However, this is a weak premise when considering interaction among anonymous self-interested agents. Whenever agents meet, there is always a decision to be made: what is the best group interaction strategy? We argue that the answer depends on the amount of information required to make a decision and on the deadline proximity for accomplishing the task in hand. In certain situations, it is to the agents’ advantage to exchange information with others, while in other situations there are no incentives for them to spend time doing so. Understanding effective behaviors according to the decision- making scenario is still an open issue in multi-agent systems. In this paper, we present a multi-agent simulator (ACoPla) to understand the correlations between agents’ interaction strategy, decision-making context and successful task accomplishment rate. Additionally, we develop a case study in the domain of site evacuation to exemplify our findings. Through this study, we detect the types of conditions under which cooperation becomes the preferred strategy, as the environment changes. 2018-06-13T00:00:00Z http://hdl.handle.net/10366/139219 The fourth industrial revolution, in which we transit, is preceded by a digital economy based fundamentally on information. And although estimates have been made on whether the data moving in the digital economy flow are from sensors or machines or come from each of us, one thing is certain, all information has a monetary value. Within this flow of information are our personal data. Every moment that we use an electronic device we leave behind vestiges of our life, which are collected by the machines to generate value to the companies. In this way our information is subject to market rules, supply and demand. We have become intangible beings, mercantilized, giving our bodies of data to the science, innovation and technological development. With the use of technologies such as Big Data and IoT, more information less is better. The speed with which our information is collected and treated as well as commercialized is undermining confidence in the digital market. Concern about the misuse of our personal data, or about the information we know about us, raises fundamental questions about privacy, ownership of information and human rights. The question of who should benefit from products and services based on digital data (generated by users) are the main uncertainties that shape the digital market opportunities. But, how can we measure trust in companies if we are not aware of the value our personal information has in the digital economy? What is the value that, as headlines, we give to our personal data? Perhaps therein lies the problem of allowing others to have power over our information. To promote the digital market and trust in it, we need to know the value of our information. Becoming aware of the fact and consequences of collecting our data, as well as its monetary value and importance in the digital economy, is the first beneficial step towards the empowerment of our information 2018-06-30T00:00:00Z http://hdl.handle.net/10366/139218 The increasing use and development of renewable energy sources and distributed generation, brought several changes to the power system operation. Electricity markets worldwide are complex and dynamic environments with very particular characteristics, resulting from their restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources. With the eminent implementation of micro grids and smart grids, new business models able to cope with the new opportunities are being developed. Virtual Power Players are a new type of player, which allows aggregating a diversity of entities, e.g. generation, storage, electric vehicles, and consumers, to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players` benefits. This paper proposes a clustering methodology regarding the remuneration and tariff of VPP. It proposes a model to implement fair and strategic remuneration and tariff methodologies, using a clustering algorithm, applied to load values, submitted to different types of normalization process, which creates sub-groups of data according to their correlations. The clustering process is evaluated so that the number of data sub-groups that brings the most added value for the decision making process is found, according to the players characteristics. The proposed clustering methodology has been tested in a real distribution network with 30 bus, including residential and commercial consumers, photovoltaic generation and storage units 2018-06-30T00:00:00Z http://hdl.handle.net/10366/139217 Face recognition is an important biometric method because of its potential applications in many fields, such as access control and surveillance. In this paper, the performance of the individual channels from the YCBCR colour space on face recognition for surveillance applications is investigated and compared with the performance of the grayscale. In addition, the performance of fusing two or more colour channels is also compared with that of the grayscale. Three cases with a different number of training images per persons were used as a test bed. It was found out that, the grayscale always outperforms the individual channel. However, the fusion of CBxCR with any other channel outperforms the grayscale when three images of the same class from the same database are used for training. Regardless of the cases used, the CBxCR channel always gave the best performance for the individual colour channels. It was found that, in general, increasing the number of fused channels increases the performance of the system. It was also found that the grayscale channel is the better choice for face recognition since it contains better quality edges and visual features which are essential for face recognition. 2018-06-30T00:00:00Z http://hdl.handle.net/10366/139216 This paper addresses the robust formation control of non-holonomic mobile robots with homogeneous system architecture and decentralized control structure. Therefore, it was necessary the mathematical modeling of mobile robots, from which, the Separation-Bearing variant of Leader-Following control strategy was implemented. The stability proof were based on the Lyapunov theory. The sliding mode control (SMC) strategy was used in the controller design to make the control robust to the incidence of uncertainties and disturbances. The Fuzzy Adaptive Formation Control is designed to eliminate the  previous bounding knowledge of these uncertainties and disturbances. The proposed control effectiveness is demonstrated by results obtained with simulations in Matlab/Simulink. The pure kinematic and kinematic with disturbances is also analyzed. The results shows the controllers effectiveness to formation of multi-robots systems to the eight-shaped trajectory. 2018-06-30T00:00:00Z http://hdl.handle.net/10366/139215 The human body has endogenous biological rhythms. One of those rhythms is the circadian rhythm, with a cycle of approximate 24 hours, that is responsible for regulating many important functions of human body. In this contribution, we propose a nonlinear coupled differential equation for modelling some agents responsible for the circadian rhythm under the influence of pain. We show results concerning the well-posedness of a solution as well as an analysis on the synchronization for each agents. We use a multi-agent simulation strategy of an corresponding model as an alternative interpretation of the pain influences in the behavior of the circadian rhythm. 2018-06-30T00:00:00Z http://hdl.handle.net/10366/139214 Smart City has an infrastructure that works with technology to reduce daily problems. The lack of parking spots is one of these problems that can be controlled by creating Smart Parking systems. The MAPS (Multi-Agent Parking System) project studies and develops multi-agent systems for smart parking using JaCaMo framework to implement agents and artifacts. This paper presents the so-called MAPS-SUMO, a middleware between the MAPS project and SUMO, a simulation tool used for urban traffic. Our middleware allows a graphical representation for the simulation executed by MAPS agents. 2018-06-30T00:00:00Z http://hdl.handle.net/10366/139213 2018-06-30T00:00:00Z