Recurrent Spiking Networks Solve Planning Tasks

Rueckert, E.; Kappel, D.; Tanneberg, D.; Pecevski, D.; Peters, J

doi:10.1038/srep21142

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Recurrent Spiking Networks Solve Planning Tasks

Rueckert, E., Kappel, D., Tanneberg, D., Pecevski, D., & Peters, J. (2016). Recurrent Spiking Networks Solve Planning Tasks. Scientific Reports, 6: 21142. doi:10.1038/srep21142.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-25EB-F Version Permalink: https://hdl.handle.net/21.11116/0000-0004-74FC-E

Genre: Journal Article

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Creators:
Rueckert, E.¹, Author
Kappel, D.¹, Author
Tanneberg, D.¹, Author
Pecevski, D.¹, Author
Peters, J², Author

Affiliations:
1External Organizations, ou_persistent22
2Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647

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Free keywords: Abt. Schölkopf

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Language(s): eng - English

Dates: Date issued: 2016-02

Publication Status: Issued

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Identifiers: DOI: 10.1038/srep21142

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Title: Scientific Reports

Abbreviation : Sci. Rep.

Source Genre: Journal

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Publ. Info: London, UK : Nature Publishing Group

Pages: - Volume / Issue: 6 Sequence Number: 21142 Start / End Page: - Identifier: ISSN: 2045-2322
CoNE: https://pure.mpg.de/cone/journals/resource/2045-2322