Soft-Reward Based Reinforcement Learning by Spiking Neural Networks

Wei Ya Shi

doi:10.4028/www.scientific.net/AMR.219-220.770

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 219-220Soft-Reward Based Reinforcement Learning by...

Soft-Reward Based Reinforcement Learning by Spiking Neural Networks

Abstract:

In this paper, we propose algorithm based reinforcement learning for spiking neural networks. The algorithm simulates biological adaptability and uses the soft-reward from environment to modulate the synaptic weight, which combines spike-timing-dependent plasticity (STDP), winner-take-all mechanism. The algorithm is tested to classify a number of standard benchmark dataset. The obtained results show the effectiveness of the proposed algorithm.

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Periodical:

Advanced Materials Research (Volumes 219-220)

Pages:

770-773

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.219-220.770

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Online since:

March 2011

Authors:

Wei Ya Shi

Keywords:

Adaptability, Reinforcement, Soft-Rewarded, Spike

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