Computing on Wheels: A Deep Reinforcement Learning-Based Approach-Reference-Cited by-同舟云学术

Computing on Wheels: A Deep Reinforcement Learning-Based Approach

Author:

Kazmi S. M. Ahsan¹^ORCID,Ho Tai Manh²^ORCID,Nguyen Tuong Tri³,Fahim Muhammad⁴^ORCID,Khan Adil⁵^ORCID,Piran Md. Jalil⁶^ORCID,Baye Gaspard⁷^ORCID

Affiliation:

1. Faculty of Computer Science and Creative Technologies, University of the West of England, Bristol, U.K.

2. Synchromedia Laboratory, École de Technologie Supérieure, Université du Québec, Montreal, QC, Canada

3. Institute of Opened Training and Information Technology, Hue University, Hue City, Vietnam

4. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, U.K.

5. Institute of Data Science and Artificial intelligence, Innopolis University, Innopolis, Russia

6. Department of Computer Science and Engineering, Sejong University, Seoul, South Korea

7. Department of Computer and Information Science (CIS), University of Massachusetts, Dartmouth, MA, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

Reference45 articles.

1. An introduction to deep reinforcement learning;françois-lavet;Found Trends Mach Learn,2019

4. Vehicular edge computing via deep reinforcement learning;qi;arXiv 1901 04290,2018

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