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. 1907.09633
  4. Cited By
Low-Variance and Zero-Variance Baselines for Extensive-Form Games

Low-Variance and Zero-Variance Baselines for Extensive-Form Games

22 July 2019
Trevor Davis
Martin Schmid
Michael Bowling
    OffRL
ArXivPDFHTML

Papers citing "Low-Variance and Zero-Variance Baselines for Extensive-Form Games"

4 / 4 papers shown
Title
A Survey on Self-play Methods in Reinforcement Learning
A Survey on Self-play Methods in Reinforcement Learning
Chao Yu
Zelai Xu
Chengdong Ma
Chao Yu
Weijuan Tu
...
Deheng Ye
Wenbo Ding
Yaodong Yang
Yu Wang
Yu Wang
SyDa
SSL
OnRL
51
8
0
02 Aug 2024
Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games: Corrections
Dustin Morrill
Ryan DÓrazio
Marc Lanctot
J. R. Wright
Michael Bowling
Amy Greenwald
51
21
0
24 May 2022
DREAM: Deep Regret minimization with Advantage baselines and Model-free
  learning
DREAM: Deep Regret minimization with Advantage baselines and Model-free learning
Eric Steinberger
Adam Lerer
Noam Brown
33
53
0
18 Jun 2020
Rethinking Formal Models of Partially Observable Multiagent Decision
  Making
Rethinking Formal Models of Partially Observable Multiagent Decision Making
Vojtěch Kovařík
Martin Schmid
Neil Burch
Michael Bowling
Viliam Lisý
OffRL
17
54
0
26 Jun 2019
1