ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2104.13446
  4. Cited By
Semi-On-Policy Training for Sample Efficient Multi-Agent Policy
  Gradients

Semi-On-Policy Training for Sample Efficient Multi-Agent Policy Gradients

27 April 2021
Bozhidar Vasilev
Tarun Gupta
Bei Peng
Shimon Whiteson
ArXivPDFHTML

Papers citing "Semi-On-Policy Training for Sample Efficient Multi-Agent Policy Gradients"

3 / 3 papers shown
Title
Centralized Model and Exploration Policy for Multi-Agent RL
Centralized Model and Exploration Policy for Multi-Agent RL
Qizhen Zhang
Chris Xiaoxuan Lu
Animesh Garg
Jakob N. Foerster
14
15
0
14 Jul 2021
MAVEN: Multi-Agent Variational Exploration
MAVEN: Multi-Agent Variational Exploration
Anuj Mahajan
Tabish Rashid
Mikayel Samvelyan
Shimon Whiteson
DRL
140
355
0
16 Oct 2019
Stabilising Experience Replay for Deep Multi-Agent Reinforcement
  Learning
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
Jakob N. Foerster
Nantas Nardelli
Gregory Farquhar
Triantafyllos Afouras
Philip Torr
Pushmeet Kohli
Shimon Whiteson
OffRL
117
595
0
28 Feb 2017
1