fnbot-07-00006.pdf (2.01 MB)
Rare neural correlations implement robotic conditioning with delayed rewards and disturbances
journal contribution
posted on 2015-03-13, 11:06 authored by Andrea SoltoggioAndrea Soltoggio, Andre Lemme, Felix Reinhart, Jochen SteilNeural 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.
Funding
This work was supported by the European Community’s Seventh Framework Programme FP7/2007-2013, Challenge 2 Cognitive Systems, Interaction, Robotics (Grant agreement No. 248311-AMARSi).
History
School
- Science
Department
- Computer Science
Published in
Frontiers in NeuroroboticsVolume
7Issue
APRCitation
SOLTOGGIO, A. ... et al., 2013. Rare neural correlations implement robotic conditioning with delayed rewards and disturbances. Frontiers in Neurorobotics, 7.Publisher
Frontiers Research FoundationVersion
- VoR (Version of Record)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/Publication date
2013Notes
This is an open access article published under CC-BY licence. © the authors.eISSN
1662-5218Publisher version
Language
- en