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This paper describes a model for an autonomous robotic agent that is capable of mapping its environment, creating a state representation and learning how to execute simple tasks using this representation. The multi-level architecture developed is composed of 3 parts. The execution level is responsible for interaction with the environment. The clustering level, which maps the input received from sensor...
This paper describes a model of visual selective attention, called NLOOK, proposed to be used in computational and robotic vision systems. This model first decomposes the visual input in a set of topographic feature maps which encode intensity, orientation, color and movement. All feature maps feed into a master ldquosaliency maprdquo, which topographically codifies for local conspicuity over the...
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