Abstract
Living organisms exhibit a strong mutual coupling between physical structure and behavior. For visual sensorimotor systems, this interrelationship is strongly reflected by the topological organization of a visual sensor and how the sensor is moved with respect to the organism’s environment. Here we present an approach which addresses simultaneously and in a unified manner i) the organization of visual sensor topologies according to given sensor-environment interaction patterns, and ii) the formation of motor movement fields adapted to specific sensor topologies. We propose that for the development of well-adapted visual sensorimotor structures, the perceptual system should optimize available resources to accurately perceive an observed phenomena, and at the same time, should co-develop sensory and motor layers such that the relationship between past and future stimuli is simplified on average. In a mathematical formulation, we implement this request as an optimization problem where the variables are the sensor topology, the layout of the motor space, and a prediction mechanism establishing a temporal relationship. We demonstrate that the same formulation is applicable for spatial self-organization of both, visual receptive fields and motor movement fields. The results demonstrate how the proposed principles can be used to develop sensory and motor systems with favorable mutual interdependencies.
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Ruesch, J., Ferreira, R., Bernardino, A. (2013). An Approach toward Self-organization of Artificial Visual Sensorimotor Structures. In: Chella, A., Pirrone, R., Sorbello, R., Jóhannsdóttir, K. (eds) Biologically Inspired Cognitive Architectures 2012. Advances in Intelligent Systems and Computing, vol 196. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34274-5_48
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DOI: https://doi.org/10.1007/978-3-642-34274-5_48
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