Recurrent Spiking Networks Solve Planning Tasks

A recurrent spiking neural network is proposed that implements planning as probabilistic inference for finite and infinite horizon tasks. The architecture splits this problem into two parts: The stochastic transient firing of the network embodies the dynamics of the planning task. With appropriate i...

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Veröffentlicht in:	Scientific reports 2016-02, Vol.6 (1), p.21142-21142, Article 21142
Hauptverfasser:	Rueckert, Elmar, Kappel, David, Tanneberg, Daniel, Pecevski, Dejan, Peters, Jan
Format:	Artikel
Sprache:	eng
Schlagworte:	631/378/116 631/378/1595 639/166/987 639/705/117 Data processing Firing pattern Humanities and Social Sciences Motor task performance multidisciplinary Neural networks Reinforcement Science Sensory neurons Stochasticity
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