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Visual objects identification is a key cognitive process for intelligent virtual agents that evolve in virtual environments. This process allows the elaboration of intern representation of the environment for cognitive manipulation and posterior intelligent response production. There exists many architectures based on memory modules for visual elements identification of environment as they were invariant, this seems to be different as real humans process visual scene. This document presents a description of visual object identification task based on current neuroscience state of the art. This work is part of a proposal of a cognitive architecture that lend us bring virtual agents with more human behaviors. Finally, we realized an implementation that shows afferent/efferent flow and processing of information of our proposed architecture.
Date of Conference: 18-20 Aug. 2011