BOOTSTRAPPING PERCEPTION USING INFORMATION THEORY: CASE STUDIES IN A QUADRUPED ROBOT RUNNING ON DIFFERENT GROUNDS
Nico M. Schmidt (),
Matej Hoffmann (),
Kohei Nakajima () and
Rolf Pfeifer ()
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Nico M. Schmidt: Artificial Intelligence Laboratory, Department of Informatics, University of Zurich, Andreasstrasse 15, 8050 Zurich, Switzerland
Matej Hoffmann: Artificial Intelligence Laboratory, Department of Informatics, University of Zurich, Andreasstrasse 15, 8050 Zurich, Switzerland
Kohei Nakajima: Artificial Intelligence Laboratory, Department of Informatics, University of Zurich, Andreasstrasse 15, 8050 Zurich, Switzerland
Rolf Pfeifer: Artificial Intelligence Laboratory, Department of Informatics, University of Zurich, Andreasstrasse 15, 8050 Zurich, Switzerland
Advances in Complex Systems (ACS), 2013, vol. 16, issue 02n03, 1-25
Abstract:
Animals and humans engage in an enormous variety of behaviors which are orchestrated through a complex interaction of physical and informational processes: The physical interaction of the bodies with the environment is intimately coupled with informational processes in the animal's brain. A crucial step toward the mastery of all these behaviors seems to be to understand the flows of information in the sensorimotor networks. In this study, we have performed a quantitative analysis in an artificial agent — a running quadruped robot with multiple sensory modalities — using tools from information theory (transfer entropy). Starting from very little prior knowledge, through systematic variation of control signals and environment, we show how the agent can discover the structure of its sensorimotor space, identify proprioceptive and exteroceptive sensory modalities, and acquire a primitive body schema. In summary, we show how the analysis of directed information flows in an agent's sensorimotor networks can be used to bootstrap its perception and development.
Keywords: Information theory; transfer entropy; perception; developmental robotics; sensorimotor contingencies; body schema (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:16:y:2013:i:02n03:n:s0219525912500786
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DOI: 10.1142/S0219525912500786
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