Abstract
While affective computing and the entertainment industry still maintain a substantial gap between themselves, biosignals are subject of digital acquisition through low budget technologic solutions at neglectable invasive levels preventing users from focusing their awareness in the equipment. The integration of electroencephalography, galvanic skin response and oximeter in a multichannel framework constitutes an effort in the path to identify emotional states via biosignals expression. In order to induce and detect specific emotions, gender specific sessions were defined based on the International Affective Picture System and performed in a controlled environment. Results granted by distinct analysis techniques showed that high frequency EEG waves are strongly related to emotions and are a solid ground to perform accurate emotion classification. They have also given strong indications that females are more sensitive to emotion induction. On the other hand, one might conclude that the attained success levels concerning relating emotions to biosignals are extremely encouraging not only to the continuation of this research topic but also to the application of these results in domains such as multimedia entertainment, advertising and medical treatments.

Abstract
The fall of chess as a main domain for Artificial Intelligence (AI) research, after the victory of Deep Blue over Kasparov, put forward robotic soccer as a new challenging domain for AI researchers. Robotic Soccer is very appropriate for researching in Distributed AI problems, e.g. coordination methodologies, whose results can later be applied to other domains. Coordination can be defined as the capability of several agents to work together as a team, in order to accomplish a common goal. In the context of robotic soccer, several aspects may benefit from appropriate coordination methodologies, since team play is decisive for winning the games. This paper presents a methodology to enable a team of robotic soccer agents to coordinate their positioning in the field, and a methodology that enables them to cooperatively execute predefined set plays (flexible plans). Both coordination methods are used in real soccer and sports in general, commonly known as formations and set plays respectively. However, its use in a team of autonomous agents is still unexplored and is a major innovation of this work. A graphical tool to define formations and set plays was fully developed in the context of this work offering a quicker and more appealing way to define both formations and set plays. The tool's interface was inspired on "blackboard" applications, used nowadays for the same purpose in real sports. The tool enables very easy definition of set plays that may then be executed in real-time during the matches. Examples of complete set plays and their practical execution are also described, showing the usefulness of the set play concept and the utility of the developed tool.

Abstract
Developed countries have made significant efforts to integrate Unmanned Aerial Vehicle (UAV) operations in controlled aerial space due to a rising interest of using UAVs for civilian as well as military purposes. This paper focuses on looking for reliable solutions and a way to validate an autonomous multiagent control system through a different variety of Flight Simulations. This study has two main lines, the first being the use of multiagent systems in UAVs, aiming at a fully autonomous control. The second and focal line is a survey about the variety of simulation systems dedicated to aerodynamics and aircrafts, comparing them and their feasibility to validate the developed multiagent control system. One critical factor is hazard situations, like emergency landing without runway or equipment failure, which should be predicted in an automated system. Most flight simulators are not realistic enough to validate a multiagent algorithm in hazard situations. At the same time, it is impossible to predict every type of failure in real world. The boundaries of simulation should be very well enclosured in order to present results using simulation.

Abstract
Many of the physically injured use electric wheelchairs as an aid to locomotion. Usually, for commanding this type of wheelchair, it is required the use of one's hands and this poses a problem to those who, besides being unable to use their legs, are also unable to properly use their hands. The aim of the work described here, is to create a prototype of a wheelchair command interface that do not require hand usage. Facial expressions were chosen instead, to provide the necessary visual information for the interface to recognize user commands. The facial expressions are captured by a digital camera and interpreted by an application running on a laptop computer on the wheelchair. The software includes digital image processing algorithms for feature detection, such as colour segmentation and edge detection, followed by the application of a neural network that uses these features to detect the desired facial expressions. A simple simulator, built on top of the known (Ciber-Mouse) was used to validate the approach by simulating the control of the intelligent wheelchair in a hospital environment. The results obtained from the platform provide strong evidence that it is possible to comfortably drive an intelligent wheelchair using facial expressions.

Abstract
While affective computing and the entertainment industry still maintain a substantial gap between themselves, biosignals are subject of digital acquisition through low budget technologic solutions at neglectable invasive levels preventing users from focusing their awareness in the equipment. The integration of electroencephalography, galvanic skin response and oximeter in a multichannel framework constitutes an effort in the path to identify emotional states via biosignals expression. In order to induce and detect specific emotions, gender specific sessions were defined based on the International Affective Picture System and performed in a controlled environment, Results granted by distinct analysis techniques showed that high frequency EEG waves are strongly related to emotions and are a solid ground to perform accurate emotion classification. They have also given strong indications that females are more sensitive to emotion induction. On the other hand, one might conclude that the attained success levels concerning relating emotions to biosignals are extremely encouraging not only to the continuation of this research topic but also to the application of these results in domains such as multimedia entertainment, advertising and medical treatments.

Abstract
Nowadays social networks are used for various recreational purposes. It is believed that every day is spent on average two hours per user in these networks games. Farmville is an application relating to one of the most successful social networks: Facebook. Farmville is a game that allows each user to use a diverse set of actions available for managing a virtual farm. However, this management quickly becomes a boring and time consuming process and often the user quits the application. In this context this project main objective is the development of a multi-agent system able to assist the player in Farmville. The system will help the user in most of his management tasks on the farm. The use of the implemented system ensures greater progress in the game, because there is a decrease in the time spent in performing the tasks enabling the user to focus on the strategies for advancing in the game.