Abstract
A soccer game can be seen as a confrontation between two teams of agents where each player, communicating with his teammates, try to interpret in the best way as possible the game situations, achieving its main goals. Today the most important factors in a soccer clubs life and in its coach success are the game results they achieve. They represent the success of the club and in many cases the coachs future. Because of that club coaches usually use automated tools to measure their teams performance all over a soccer competition. Based only in Cartesian coordinates and in a sequential time frame analysis, this research work presents an automatic tool capable to calculate many technical aspects in a soccer match. For the validation tool process, games of simulation 2d RoboCup international competition were used. The results achieved were quite satisfactory. In what concerns to the set of statistics collected more than 92% of the total events were detected and only for the shot event this number dropped to between 74% and 85%. The future work will be concerned in incorporating this project with a real time tracking system and increasing the number of technical aspects calculated by the system. © 2010 IEEE.

Abstract
Machine Learning (ML) and Knowledge Discovery (KD) are research areas with several different applications but that share a common objective of acquiring more and new information from data. This paper presents an application of several ML techniques in the identification of the opponent team and also on the classification of robotic soccer formations in the context of RoboCup international robotic soccer competition. RoboCup international project includes several distinct leagues were teams composed by different types of real or simulated robots play soccer games following a set of pre-established rules. The simulated 2D league uses simulated robots encouraging research on artificial intelligence methodologies like high-level coordination and machine learning techniques. The experimental tests performed, using four distinct datasets, enabled us to conclude that the Support Vector Machines (SVM) technique has higher accuracy than the k-Nearest Neighbor, Neural Networks and Kernel Naïve Bayes in terms of adaptation to a new kind of data. Also, the experimental results enable to conclude that using the Principal Component Analysis SVM achieves worse results than using simpler methods that have as primary assumption the distance between samples, like k-NN. © 2010 IEEE.

Abstract

Abstract
The present paper describes a Distributed Surveillance System that has the ability to detect, track and snapshot subjects moving around in a certain space. The system is composed by several surveillance agents and a central surveillance agent which communicates with them and process data. The surveillance agents are composed by a camera and a computer with wireless communication. The central surveillance agent runs on a computer also with wireless communication. In order to support the communication between the two types of agents, was created a language called VigilLANG. This language allows a high-level communication interface between the several surveillance agents and the central surveillance agent. The proposed surveillance system performs robust image segmentation providing the user images with the relevant information; provides robust subject detection and identification; supports expansion; etc. The system is totally configurable through the definition of new surveillance policies and may be easily expanded through the addition of new surveillance agents. The system was validated by performing a vast set of experiments, achieving very good results in the detection and position estimation of the subjects under surveillance.

Abstract
This paper presents the Advanced Collaborative Educational Model (ACEM) for conception of collaborative learning activities. It is based on collaboration between teachers through virtual interactions, reutilization, interoperability and adaptability of learning activities. The definition of learning activity is oriented to a constructivist approach. Tagging collaboration and ontologies are also considered in order to facilitate sharing knowledge in a more effective and personalized way. The main goal of this research is to describe teachers' procedures when interacting with the collaborative environment and to develop mechanisms to support teachers in their tasks, mainly in the creation of learning activities to be used in an e-learning context. The model will be implemented through a high-level graphical tool that facilitates synchronous and asynchronous communication. © 2011 IEEE.

Abstract
Strategic planning and multi-agent coordination are major research topics in the domain of RoboCup. Innovations in these areas are, however, often developed and applied to only a single RoboCup league and/or one domain, without proper generalization. Moreover, the more technical leagues, like middle-size and humanoid, tend to focus development on low-level skills, that often suffice to gain a competitive edge over other teams. In these leagues, the development of high-level cooperation is secondary. Although the importance of the concept of Setplay, to structure a robotic soccer team behaviour, has been acknowledged by many researchers, no general framework for the development and execution of generic Setplays has been introduced in the context of RoboCup. This paper presents such a framework for high-level Setplay definition and execution, applicable to any RoboCup cooperative league and similar domains. The framework is based on a flexible, standard and league-independent language, which defines Setplays that are interpreted and executed at run-time, using inter-robot communication. An initial major step in the development of the Setplay framework was its usage and testing in the scope of the FCPortugal team, which participates in the RoboCup 2D-simulation and 3D-simulation leagues, where it won several titles both in the 2D and 3D leagues. This framework was also recently implemented in the middle-size team CAMBADA. This team has, in the recent past and with previous versions of the control software, ranked first and third in RoboCup's 2008 and 2009 editions. The implementation is described with concrete examples of Setplay definition and execution, which shows the usefulness of this approach and motivate its use as a major coordination tool for teams participating in the simulation, small-size, middle-size, standard platform and humanoid leagues of RoboCup.