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2210.07636
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Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement Learning
14 October 2022
Jifeng Hu
Yanchao Sun
Hechang Chen
Sili Huang
Haiyin Piao
Yi-Ju Chang
Lichao Sun
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Papers citing
"Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement Learning"
47 / 47 papers shown
Title
Transfer RL across Observation Feature Spaces via Model-Based Regularization
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Multimodal Reward Shaping for Efficient Exploration in Reinforcement Learning
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Mon-on Pun
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Yi Chen
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19 Jul 2021
Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL
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Ruijie Zheng
Yongyuan Liang
Furong Huang
AAML
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63
0
09 Jun 2021
Reward prediction for representation learning and reward shaping
Hlynur Davíð Hlynsson
Laurenz Wiskott
OffRL
AI4TS
27
3
0
07 May 2021
Outcome-Driven Reinforcement Learning via Variational Inference
Tim G. J. Rudner
Vitchyr H. Pong
R. McAllister
Y. Gal
Sergey Levine
50
20
0
20 Apr 2021
RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents
Wei Qiu
Xinrun Wang
Runsheng Yu
Xu He
Rongpin Wang
Bo An
S. Obraztsova
Zinovi Rabinovich
37
50
0
16 Feb 2021
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning
Wei-Fang Sun
Cheng-Kuang Lee
Chun-Yi Lee
OffRL
15
49
0
16 Feb 2021
Disturbing Reinforcement Learning Agents with Corrupted Rewards
Rubén Majadas
Javier A. García
Fernando Fernández
AAML
40
6
0
12 Feb 2021
Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels
Zhaowei Zhu
Yiwen Song
Yang Liu
NoLa
39
92
0
10 Feb 2021
Provably End-to-end Label-Noise Learning without Anchor Points
Xuefeng Li
Tongliang Liu
Bo Han
Gang Niu
Masashi Sugiyama
NoLa
141
123
0
04 Feb 2021
A Second-Order Approach to Learning with Instance-Dependent Label Noise
Zhaowei Zhu
Tongliang Liu
Yang Liu
NoLa
52
127
0
22 Dec 2020
Federated Bandit: A Gossiping Approach
Zhaowei Zhu
Jingxuan Zhu
Ji Liu
Yang Liu
FedML
175
83
0
24 Oct 2020
Policy Learning Using Weak Supervision
Jingkang Wang
Hongyi Guo
Zhaowei Zhu
Yang Liu
OffRL
43
14
0
05 Oct 2020
Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics
Yanchao Sun
Da Huo
Furong Huang
AAML
OffRL
OnRL
49
49
0
02 Sep 2020
Weakly-Supervised Reinforcement Learning for Controllable Behavior
Lisa Lee
Benjamin Eysenbach
Ruslan Salakhutdinov
S. Gu
Chelsea Finn
SSL
44
26
0
06 Apr 2020
TempLe: Learning Template of Transitions for Sample Efficient Multi-task RL
Yanchao Sun
Xiangyu Yin
Furong Huang
OffRL
18
16
0
16 Feb 2020
Can Agents Learn by Analogy? An Inferable Model for PAC Reinforcement Learning
Yanchao Sun
Furong Huang
31
4
0
21 Dec 2019
Dota 2 with Large Scale Deep Reinforcement Learning
OpenAI OpenAI
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Christopher Berner
Greg Brockman
Brooke Chan
...
Szymon Sidor
Ilya Sutskever
Jie Tang
Filip Wolski
Susan Zhang
GNN
VLM
CLL
AI4CE
LRM
72
1,805
0
13 Dec 2019
Multi-Agent Game Abstraction via Graph Attention Neural Network
Y. Liu
Weixun Wang
Yujing Hu
Jianye Hao
Xingguo Chen
Yang Gao
32
239
0
25 Nov 2019
Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning
Praveen Palanisamy
45
142
0
11 Nov 2019
WATTNet: Learning to Trade FX via Hierarchical Spatio-Temporal Representation of Highly Multivariate Time Series
Jinho Lee
Seokho Yi
Jaewoo Kang
AI4TS
30
15
0
24 Sep 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift
Yaniv Ovadia
Emily Fertig
Jie Jessie Ren
Zachary Nado
D. Sculley
Sebastian Nowozin
Joshua V. Dillon
Balaji Lakshminarayanan
Jasper Snoek
UQCV
133
1,677
0
06 Jun 2019
Statistics and Samples in Distributional Reinforcement Learning
Mark Rowland
Robert Dadashi
Saurabh Kumar
Rémi Munos
Marc G. Bellemare
Will Dabney
OffRL
31
89
0
21 Feb 2019
Actor-Attention-Critic for Multi-Agent Reinforcement Learning
Shariq Iqbal
Fei Sha
48
743
0
05 Oct 2018
Reinforcement Learning with Perturbed Rewards
Jingkang Wang
Yang Liu
Yue Liu
NoLa
45
127
0
02 Oct 2018
Combined Reinforcement Learning via Abstract Representations
Vincent François-Lavet
Yoshua Bengio
Doina Precup
Joelle Pineau
OffRL
44
89
0
12 Sep 2018
Learning Dexterous In-Hand Manipulation
OpenAI OpenAI
Marcin Andrychowicz
Bowen Baker
Maciek Chociej
Rafal Jozefowicz
...
Szymon Sidor
Joshua Tobin
Peter Welinder
Lilian Weng
Wojciech Zaremba
68
1,865
0
01 Aug 2018
Reward Estimation for Variance Reduction in Deep Reinforcement Learning
Joshua Romoff
Peter Henderson
Alexandre Piché
Vincent François-Lavet
Joelle Pineau
54
42
0
09 May 2018
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Tabish Rashid
Mikayel Samvelyan
Christian Schroeder de Witt
Gregory Farquhar
Jakob N. Foerster
Shimon Whiteson
118
1,662
0
30 Mar 2018
Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning
Vladimir Feinberg
Alvin Wan
Ion Stoica
Michael I. Jordan
Joseph E. Gonzalez
Sergey Levine
OffRL
45
317
0
28 Feb 2018
Learning the Reward Function for a Misspecified Model
Erik Talvitie
37
10
0
29 Jan 2018
Inverse Reward Design
Dylan Hadfield-Menell
S. Milli
Pieter Abbeel
Stuart J. Russell
Anca Dragan
57
393
0
08 Nov 2017
Distributional Reinforcement Learning with Quantile Regression
Will Dabney
Mark Rowland
Marc G. Bellemare
Rémi Munos
68
753
0
27 Oct 2017
A Distributional Perspective on Reinforcement Learning
Marc G. Bellemare
Will Dabney
Rémi Munos
OffRL
65
1,497
0
21 Jul 2017
Proximal Policy Optimization Algorithms
John Schulman
Filip Wolski
Prafulla Dhariwal
Alec Radford
Oleg Klimov
OffRL
201
18,685
0
20 Jul 2017
Imagination-Augmented Agents for Deep Reinforcement Learning
T. Weber
S. Racanière
David P. Reichert
Lars Buesing
A. Guez
...
Razvan Pascanu
Peter W. Battaglia
Demis Hassabis
David Silver
Daan Wierstra
LM&Ro
65
552
0
19 Jul 2017
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
Ryan J. Lowe
Yi Wu
Aviv Tamar
J. Harb
Pieter Abbeel
Igor Mordatch
113
4,441
0
07 Jun 2017
Reinforcement Learning with a Corrupted Reward Channel
Tom Everitt
Victoria Krakovna
Laurent Orseau
Marcus Hutter
Shane Legg
66
100
0
23 May 2017
Model-Based Planning with Discrete and Continuous Actions
Mikael Henaff
William F. Whitney
Yann LeCun
48
16
0
19 May 2017
The Predictron: End-To-End Learning and Planning
David Silver
H. V. Hasselt
Matteo Hessel
Tom Schaul
A. Guez
...
Gabriel Dulac-Arnold
David P. Reichert
Neil C. Rabinowitz
André Barreto
T. Degris
40
289
0
28 Dec 2016
Continuous control with deep reinforcement learning
Timothy Lillicrap
Jonathan J. Hunt
Alexander Pritzel
N. Heess
Tom Erez
Yuval Tassa
David Silver
Daan Wierstra
168
13,174
0
09 Sep 2015
Learning in the Presence of Corruption
Brendan van Rooyen
Robert C. Williamson
23
17
0
01 Apr 2015
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
624
149,474
0
22 Dec 2014
Training Convolutional Networks with Noisy Labels
Sainbayar Sukhbaatar
Joan Bruna
Manohar Paluri
Lubomir D. Bourdev
Rob Fergus
NoLa
53
270
0
09 Jun 2014
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih
Koray Kavukcuoglu
David Silver
Alex Graves
Ioannis Antonoglou
Daan Wierstra
Martin Riedmiller
83
12,163
0
19 Dec 2013
Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
Gilles Blanchard
Marek Flaska
G. Handy
Sara Pozzi
Clayton Scott
NoLa
51
243
0
05 Mar 2013
Variance-Based Rewards for Approximate Bayesian Reinforcement Learning
Jonathan Sorg
Satinder Singh
Richard L. Lewis
OffRL
60
69
0
15 Mar 2012
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