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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2dmkezwdzrcofn7zdzzte2h75i" style="color: black;">2009 IEEE Congress on Evolutionary Computation</a>
Active perception refers to a theoretical approach to the study of perception grounded on the idea that perceiving is a way of acting, rather than a cognitive process whereby the brain constructs an internal representation of the world. The operational principles of active perception can be effectively tested by building robot-based models in which the relationship between perceptual categories and the body-environment interactions can be experimentally manipulated. In this paper, we study the<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cec.2009.4982927">doi:10.1109/cec.2009.4982927</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cec/TuciMN09.html">dblp:conf/cec/TuciMN09</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pov7rilcdbcdxhueqqk33wrwey">fatcat:pov7rilcdbcdxhueqqk33wrwey</a> </span>
more »... echanisms of tactile perception in a task in which a neurocontrolled anthropomorphic robotic arm, equipped with coarse-grained tactile sensors, is required to perceptually discriminate between spherical and ellipsoid objects. The results of this work demonstrate that evolved continuous time non-linear neural controllers can bring forth strategies to allow the arm to effectively solve the discrimination task. * E. Tuci, G. Massera, and S. Nolfi are with the
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