A framework for learning in humanoid simulated robots

One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.

An Optimum-Path Forest framework for intrusion detection in computer networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Learning strategies evaluation in students with attention deficit hyperactivity disorder

This study aim to verify the use of learning strategies in students of the elementary level presenting interdisciplinary diagnosis of attention dei cit hyperactivity disorder (ADHD). Nine students, male gender, attending 3rd to 9th grade level of the elementary level, average age 10 years and 7 months, presenting interdisciplinary diagnosis of attention dei cit hyperactivity disorder (ADHD). h e students were submitted to the application of the Evaluation of Learning Strategies from elementary level – EAVAP-EF – scale, which aimed to evaluate the strategies reported and used by students in situation of study and learning, as follows: cognitive strategies, metacognitive strategies and absence of dysfunctional metacognitive strategies. h e general result at EAVAP-EF scale, showed that students with ADHD reached the percentile 25%, considered as low performance in the use of the learning strategies. For the variable absence of dysfunctional metacognitive strategies, the students presented percentile 30%, percentile 25% for cognitive strategies and 55% for metacognitive strategies. h e results showed that ADHD students do not use ef ectively the learning cognitive and metacognitive strategies and present the use of dysfunctional metacognitive strategies. h ese alterations match with the framework of ADHD because the entry of information, either visual or auditory, showed alterations, derived from inattention, which af ected the learning in classroom situation.