BrainQN: Enhancing the Robustness of Deep Reinforcement Learning with Spiking Neural Networks

As the third‐generation network succeeding artificial neural networks (ANNs), spiking neural networks (SNNs) offer high robustness and low energy consumption. Inspired by biological systems, the limitations of low robustness and high‐power consumption in deep reinforcement learning (DRL) are address...

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Xehetasun bibliografikoak
Egile Nagusiak:	Shuo Feng, Jian Cao, Zehong Ou, Guang Chen, Yi Zhong, Zilin Wang, Juntong Yan, Jue Chen, Bingsen Wang, Chenglong Zou, Zebang Feng, Yuan Wang
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Wiley 2024-09-01
Saila:	Advanced Intelligent Systems
Gaiak:	deep reinforcement learning efficiency neuromorphic chips robustness spiking neural networks
Sarrera elektronikoa:	https://doi.org/10.1002/aisy.202400075
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

BrainQN: Enhancing the Robustness of Deep Reinforcement Learning with Spiking Neural Networks

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