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Representation Learning For Efficient Deep Multi-Agent Reinforcement
  Learning

Representation Learning For Efficient Deep Multi-Agent Reinforcement Learning

5 June 2024
Dom Huh
Prasant Mohapatra
ArXivPDFHTML

Papers citing "Representation Learning For Efficient Deep Multi-Agent Reinforcement Learning"

6 / 6 papers shown
Title
Attention-Guided Contrastive Role Representations for Multi-Agent
  Reinforcement Learning
Attention-Guided Contrastive Role Representations for Multi-Agent Reinforcement Learning
Zican Hu
Zongzhang Zhang
Huaxiong Li
Chunlin Chen
Hongyu Ding
Zhi Wang
45
4
0
08 Dec 2023
Towards a Standardised Performance Evaluation Protocol for Cooperative
  MARL
Towards a Standardised Performance Evaluation Protocol for Cooperative MARL
R. Gorsane
Omayma Mahjoub
Ruan de Kock
Roland Dubb
Siddarth S. Singh
Arnu Pretorius
OffRL
36
48
0
21 Sep 2022
Sample-Efficient Multi-Agent Reinforcement Learning with Demonstrations
  for Flocking Control
Sample-Efficient Multi-Agent Reinforcement Learning with Demonstrations for Flocking Control
Yunbo Qiu
Yuzhu Zhan
Yue Jin
Jian Wang
Xudong Zhang
13
6
0
17 Sep 2022
Decoupling Representation Learning from Reinforcement Learning
Decoupling Representation Learning from Reinforcement Learning
Adam Stooke
Kimin Lee
Pieter Abbeel
Michael Laskin
SSL
DRL
255
337
0
14 Sep 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
229
3,029
0
09 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
245
9,042
0
06 Jun 2015
1