Rare neural correlations implement robotic conditioning with reward delays and disturbances

Soltoggio A, Lemme A, Reinhart F, Steil JJ (2013)
Frontiers in Neurorobotics 7.

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Journal Article | Published | English
Abstract
Neural conditioning associates cues and actions with following rewards. The environments in which robots operate, however, are pervaded by a variety of disturbing stimuli and uncertain timing. In particular, variable reward delays make it difficult to reconstruct which previous actions are responsible for following rewards. Such an uncertainty is handled by biological neural networks, but represents a challenge for computational models, suggesting the lack of a satisfactory theory for robotic neural conditioning. The present study demonstrates the use of rare neural correlations in making correct associations between rewards and previous cues or actions. Rare correlations are functional in selecting sparse synapses to be eligible for later weight updates if a reward occurs. The repetition of this process singles out the associating and reward-triggering pathways, and thereby copes with distal rewards. The neural network displays macro-level classical and operant conditioning, which is demonstrated in an interactive real-life human-robot interaction. The proposed mechanism models realistic conditioning in humans and animals and implements similar behaviors in neuro-robotic platforms.
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Article Processing Charge funded by the Deutsche Forschungsgemeinschaft and the Open Access Publication Fund of Bielefeld University.
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Soltoggio A, Lemme A, Reinhart F, Steil JJ. Rare neural correlations implement robotic conditioning with reward delays and disturbances. Frontiers in Neurorobotics. 2013;7.
Soltoggio, A., Lemme, A., Reinhart, F., & Steil, J. J. (2013). Rare neural correlations implement robotic conditioning with reward delays and disturbances. Frontiers in Neurorobotics, 7.
Soltoggio, A., Lemme, A., Reinhart, F., and Steil, J. J. (2013). Rare neural correlations implement robotic conditioning with reward delays and disturbances. Frontiers in Neurorobotics 7.
Soltoggio, A., et al., 2013. Rare neural correlations implement robotic conditioning with reward delays and disturbances. Frontiers in Neurorobotics, 7.
A. Soltoggio, et al., “Rare neural correlations implement robotic conditioning with reward delays and disturbances”, Frontiers in Neurorobotics, vol. 7, 2013.
Soltoggio, A., Lemme, A., Reinhart, F., Steil, J.J.: Rare neural correlations implement robotic conditioning with reward delays and disturbances. Frontiers in Neurorobotics. 7, (2013).
Soltoggio, Andrea, Lemme, Andre, Reinhart, Felix, and Steil, Jochen J. “Rare neural correlations implement robotic conditioning with reward delays and disturbances”. Frontiers in Neurorobotics 7 (2013).
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Editorial: Neural plasticity for rich and uncertain robotic information streams.
Soltoggio A, van der Velde F., Front Neurorobot 9(), 2015
PMID: 26578947
Self-organizing neural integration of pose-motion features for human action recognition.
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Value and reward based learning in neurorobots.
Krichmar JL, Rohrbein F., Front Neurorobot 7(), 2013
PMID: 24062683

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