In‐Memory Realization of Eligibility Traces Based on Conductance Drift of Phase Change Memory for Energy‐Efficient Reinforcement Learning-Reference-Cited by-同舟云学术

In‐Memory Realization of Eligibility Traces Based on Conductance Drift of Phase Change Memory for Energy‐Efficient Reinforcement Learning

Published:2021-12-16 Issue:6 Volume:34 Page:2107811
ISSN:0935-9648
Container-title:Advanced Materials
language:en
Short-container-title:Advanced Materials

Author:

Lu Yingming¹,Li Xi²,Yan Bonan³,Yan Longhao¹,Zhang Teng¹,Song Zhitang²,Huang Ru¹³⁴,Yang Yuchao¹³⁴^ORCID

Affiliation:

1. Key Laboratory of Microelectronic Devices and Circuits (MOE) School of Integrated Circuits Peking University Beijing 100871 China

2. Shanghai Key Laboratory of Nanofabrication Technology for Memory Shanghai Institute of Micro‐system and Information Technology Chinese Academy of Sciences Shanghai 200050 China

3. Center for Brain Inspired Chips Institute for Artificial Intelligence Peking University Beijing 100871 China

4. Center for Brain Inspired Intelligence Chinese Institute for Brain Research (CIBR), Beijing Beijing 102206 China

Funder

National Natural Science Foundation of China

Higher Education Discipline Innovation Project

Publisher

Wiley

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adma.202107811

Reference54 articles.

1. Reinforcement Learning: A Survey

2. Human-level control through deep reinforcement learning

3. Mastering the game of Go with deep neural networks and tree search

4. Mastering the game of Go without human knowledge

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