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researcher

Rui Wang

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.NE2
  • cs.AI1
  • cs.LG1
same name
  • Rui Wang — 24 papers, h 33
  • Rui Wang — 22 papers
  • Rui Wang — 19 papers, h 32
  • Rui Wang — 11 papers, h 15
  • Rui Wang — 11 papers, h 20
  • Rui Wang — 11 papers, h 15

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192022
most citedDeep Reinforcement Learning for Online Routing of Unmanned Aerial Vehicles with Wireless Power Transfer

3 citations · 3 across the 1 of their papers we have counts for

collaborators

4 papers

cs.LG2022★ 3 cited

Deep Reinforcement Learning for Online Routing of Unmanned Aerial Vehicles with Wireless Power Transfer

Kaiwen Li, Tao Zhang, Rui Wang +1

The unmanned aerial vehicle (UAV) plays an vital role in various applications such as delivery, military mission, disaster rescue, communication, etc., due to its flexibility and v…

cs.NE2021

Deep Reinforcement Learning for Combinatorial Optimization: Covering Salesman Problems

Kaiwen Li, Tao Zhang, Rui Wang Yuheng Wang +1

This paper introduces a new deep learning approach to approximately solve the Covering Salesman Problem (CSP). In this approach, given the city locations of a CSP as input, a deep…

cs.AI2020

Investigating Constraint Relationship in Evolutionary Many-Constraint Optimization

Mengjun Ming, Rui Wang, Tao Zhang

This paper contributes to the treatment of extensive constraints in evolutionary many-constraint optimization through consideration of the relationships between pair-wise constrain…

cs.NE2019

Deep Reinforcement Learning for Multi-objective Optimization

Kaiwen Li, Tao Zhang, Rui Wang

This study proposes an end-to-end framework for solving multi-objective optimization problems (MOPs) using Deep Reinforcement Learning (DRL), that we call DRL-MOA. The idea of deco…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.