A reinforcement learning-based routing algorithm for large street networks-Reference-Cited by-同舟云学术

A reinforcement learning-based routing algorithm for large street networks

Author:

Li Diya¹,Zhang Zhe¹²^ORCID,Alizadeh Bahareh³,Zhang Ziyi²,Duffield Nick²⁴,Meyer Michelle A.⁵,Thompson Courtney M.¹,Gao Huilin⁶,Behzadan Amir H.³

Affiliation:

1. Department of Geography, Texas A&M University, College Station, TX, USA

2. Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA

3. Department of Construction Science, Texas A&M University, College Station, TX, USA

4. Texas A&M Institute of Data Science, College Station, TX, USA

5. Department of Landscape Architecture & Urban Planning, Texas A&M University, College Station, TX, USA

6. Department of Civil & Environmental Engineering, Texas A&M University, College Station, TX, USA

Funder

National Oceanic and Atmospheric Administration (NOAA), U.S. Department of Commerce

Texas A&M TAMIDS Data Resource Development Program

Publisher

Informa UK Limited

Subject

Library and Information Sciences,Geography, Planning and Development,Information Systems

Link

Reference111 articles.

1. Abe K. et al. 2019. Solving np-hard problems on graphs by reinforcement learning without domain knowledge. ArXiv abs/1905.11623 .

2. Agarap A.F. 2018. Deep learning using rectified linear units (relu). arXiv preprint arXiv:1803.08375 .

4. Alizadeh B. et al. 2021. Feasibility study of urban flood mapping using traffic signs for route optimization. arXiv preprint arXiv:2109.11712 .