Grounding Perception: A Developmental Approach to Sensorimotor Contingencies

October 03, 2018 ยท Declared Dead ยท ๐Ÿ› IEEE/RJS International Conference on Intelligent RObots and Systems

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Authors Alban Laflaquiรจre, Nikolas Hemion, Michaรซl Garcia Ortiz, Jean-Christophe Baillie arXiv ID 1810.01870 Category cs.LG: Machine Learning Cross-listed cs.AI, cs.RO, stat.ML Citations 5 Venue IEEE/RJS International Conference on Intelligent RObots and Systems Last Checked 4 months ago
Abstract
Sensorimotor contingency theory offers a promising account of the nature of perception, a topic rarely addressed in the robotics community. We propose a developmental framework to address the problem of the autonomous acquisition of sensorimotor contingencies by a naive robot. While exploring the world, the robot internally encodes contingencies as predictive models that capture the structure they imply in its sensorimotor experience. Three preliminary applications are presented to illustrate our approach to the acquisition of perceptive abilities: discovering the environment, discovering objects, and discovering a visual field.
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