Exploration in neo-Hebbian reinforcement learning: Computational approaches to the exploration-exploitation balance with bio-inspired neural networks. | D2R Server publishing the DBLP Bibliography Database, hosted at L3S Research Center

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dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Anthony_S._Maida>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Anthony_Triche>
dc:creator	<https://dblp.l3s.de/d2r/resource/authors/Ashok_Kumar>
foaf:homepage	<http://dx.doi.org/doi.org%2F10.1016%2Fj.neunet.2022.03.021>
foaf:homepage	<https://doi.org/10.1016/j.neunet.2022.03.021>
dc:identifier	DBLP journals/nn/TricheMK22 (xsd:string)
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dcterms:issued	2022 (xsd:gYear)
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rdfs:label	Exploration in neo-Hebbian reinforcement learning: Computational approaches to the exploration-exploitation balance with bio-inspired neural networks. (xsd:string)
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foaf:maker	<https://dblp.l3s.de/d2r/resource/authors/Ashok_Kumar>
swrc:pages	16-33 (xsd:string)
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dc:title	Exploration in neo-Hebbian reinforcement learning: Computational approaches to the exploration-exploitation balance with bio-inspired neural networks. (xsd:string)
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