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Dongming Wang

5 papers hereh-index 00 citations6 works total

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

author position
  • first author1
  • middle author4

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.MA4
  • eess.SY1
same name
  • Dongming Wang — 4 papers, h 4
  • Dongming Wang — 3 papers, h 3
  • Dongming Wang — 2 papers, h 6
  • Dongming Wang — 2 papers, h 1
  • Dongming Wang — 1 paper, h 2
  • Dongming Wang — 1 paper, h 2

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

collaborators
Showing cs.MAShow all

4 papers · 1 filter

cs.MA2026

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces

Dongming Wang, Pengcheng Dai, Wenwu Yu +1

We develop the Continuous Distributed Coupled Policy Gradient (CDCPG) algorithm for cooperative reinforcement learning in networked Markov decision processes with continuous state…

cs.MA2026

Distributed Zeroth-Order Policy Gradient for Networked Multi-agent Reinforcement Learning from Human Feedback

Pengcheng Dai, He Wang, Dongming Wang +2

We study a networked multi-agent reinforcement learning (NMARL) problem with human feedback in an infinite-horizon setting, where agents interact over an underlying network with lo…

cs.MA2025

Distributed scalable coupled policy algorithm for networked multi-agent reinforcement learning

Pengcheng Dai, Dongming Wang, Wenwu Yu +1

This paper studies networked multi-agent reinforcement learning (NMARL) with interdependent rewards and coupled policies. In this setting, each agent's reward depends on its own st…

cs.MA2025

Distributed primal-dual algorithm for constrained multi-agent reinforcement learning under coupled policies

Pengcheng Dai, He Wang, Dongming Wang +1

This paper investigates constrained multi-agent reinforcement learning (CMARL) in coupled environments, where agents collaboratively maximize the sum of local objectives while sati…

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