Luiz Marcos Garcia Gonçalves

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— In this work we propose a new paradigm for learning coordination in multi-agent systems. This approach is based on social interaction of people, specially in the fact that people communicate to each other what they think about their actions and this opinion has some influence in the behavior of each other. We propose a model in which multi-agents learn to(More)
In this work we propose two behavioraly active policies for attentional control. These policies must act based on a multi-modal sensory feedback. Two approaches are used to derive the policies: the first one follows a simple straightforward strategy and the second one uses Q-learning to learn a policy based on the perceptual state of the system. As(More)
This work describes the architecture of an integrated multi-modal sensory (vision and touch) computational system. We propose to use an approach based on robotics control theory that is motivated by biology and developmental psychology, in order to integrate the haptic and visual information processing. We show some results carried out in simulation and(More)
— We propose a new approach to reduce and abstract visual data useful for robotics applications. Basically, a moving fovea in combination with a multi-resolution representation is created from a pair of input images given by a stereo head, that reduces hundreds of times the amount of information from the original images. With this new theoretical approach(More)
In this work we propose a new approach for fast visualization and exploration of virtual worlds based on the use of cartographic concepts and techniques. Versions of cartographic maps with different levels of details can be created by using a set of operations named cartographic generalization. Car-tographic generalization employs twelve operators and(More)
1 Introduction In this work, vision and touch (artiicial) senses are integrated in a cooperative active system. Multi-modal sensory information acquired on-line is used by a robotic agent to perform real-time tasks involving categorization of objects. The visual-touch system proposed is able to foveate (verge) the eyes onto an object, to move the arms to(More)
We present mechanisms for attention control and pattern categorization as the basis for robot cognition. For attention, we gather information from attentional feature maps extracted from sensory data constructing salience maps to decide where to foveate. For iden-tiication, multi-feature maps are used as input to an associative memory, allowing the system(More)