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Combining No-regret and Q-learning

Combining No-regret and Q-learning

7 October 2019
Ian A. Kash
Michael Sullins
Katja Hofmann
    OffRL
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Papers citing "Combining No-regret and Q-learning"

26 / 26 papers shown
Title
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
58
21
0
24 May 2022
Last-iterate convergence rates for min-max optimization
Last-iterate convergence rates for min-max optimization
Jacob D. Abernethy
Kevin A. Lai
Andre Wibisono
54
74
0
05 Jun 2019
Stable-Predictive Optimistic Counterfactual Regret Minimization
Stable-Predictive Optimistic Counterfactual Regret Minimization
Gabriele Farina
Christian Kroer
Noam Brown
Tuomas Sandholm
56
34
0
13 Feb 2019
Learning to Collaborate in Markov Decision Processes
Learning to Collaborate in Markov Decision Processes
Goran Radanović
R. Devidze
David C. Parkes
Adish Singla
60
33
0
23 Jan 2019
Double Neural Counterfactual Regret Minimization
Double Neural Counterfactual Regret Minimization
Hui Li
Kailiang Hu
Zhibang Ge
Tao Jiang
Yuan Qi
Le Song
37
52
0
27 Dec 2018
Regret Circuits: Composability of Regret Minimizers
Regret Circuits: Composability of Regret Minimizers
Krishna Kumar Singh
Aron Sarmasi
Tuomas Sandholm
25
3
0
06 Nov 2018
Deep Counterfactual Regret Minimization
Deep Counterfactual Regret Minimization
Noam Brown
Adam Lerer
Sam Gross
Tuomas Sandholm
43
213
0
01 Nov 2018
Actor-Critic Policy Optimization in Partially Observable Multiagent
  Environments
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments
S. Srinivasan
Marc Lanctot
V. Zambaldi
Julien Perolat
K. Tuyls
Rémi Munos
Michael Bowling
30
148
0
21 Oct 2018
Solving Imperfect-Information Games via Discounted Regret Minimization
Solving Imperfect-Information Games via Discounted Regret Minimization
Noam Brown
Tuomas Sandholm
100
166
0
11 Sep 2018
Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max
  Optimization
Last-Iterate Convergence: Zero-Sum Games and Constrained Min-Max Optimization
C. Daskalakis
Ioannis Panageas
40
178
0
11 Jul 2018
Is Q-learning Provably Efficient?
Is Q-learning Provably Efficient?
Chi Jin
Zeyuan Allen-Zhu
Sébastien Bubeck
Michael I. Jordan
OffRL
52
801
0
10 Jul 2018
Training GANs with Optimism
Training GANs with Optimism
C. Daskalakis
Andrew Ilyas
Vasilis Syrgkanis
Haoyang Zeng
83
514
0
31 Oct 2017
Regret Minimization for Partially Observable Deep Reinforcement Learning
Regret Minimization for Partially Observable Deep Reinforcement Learning
Peter H. Jin
Kurt Keutzer
Sergey Levine
38
51
0
31 Oct 2017
Cycles in adversarial regularized learning
Cycles in adversarial regularized learning
P. Mertikopoulos
Christos H. Papadimitriou
Georgios Piliouras
27
319
0
08 Sep 2017
Monte-Carlo Tree Search by Best Arm Identification
Monte-Carlo Tree Search by Best Arm Identification
E. Kaufmann
Wouter M. Koolen
44
37
0
09 Jun 2017
A unified view of entropy-regularized Markov decision processes
A unified view of entropy-regularized Markov decision processes
Gergely Neu
Anders Jonsson
Vicencc Gómez
82
255
0
22 May 2017
DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker
DeepStack: Expert-Level Artificial Intelligence in No-Limit Poker
Matej Moravcík
Martin Schmid
Neil Burch
Viliam Lisý
Dustin Morrill
Nolan Bard
Trevor Davis
Kevin Waugh
Michael Bradley Johanson
Michael Bowling
BDL
61
904
0
06 Jan 2017
Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning
  with Stochastic Initial States
Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial States
William H. Montgomery
Anurag Ajay
Chelsea Finn
Pieter Abbeel
Sergey Levine
OnRL
53
37
0
04 Oct 2016
On Lower Bounds for Regret in Reinforcement Learning
On Lower Bounds for Regret in Reinforcement Learning
Ian Osband
Benjamin Van Roy
52
101
0
09 Aug 2016
Deep Reinforcement Learning from Self-Play in Imperfect-Information
  Games
Deep Reinforcement Learning from Self-Play in Imperfect-Information Games
Johannes Heinrich
David Silver
SSL
33
397
0
03 Mar 2016
Increasing the Action Gap: New Operators for Reinforcement Learning
Increasing the Action Gap: New Operators for Reinforcement Learning
Marc G. Bellemare
Georg Ostrovski
A. Guez
Philip S. Thomas
Rémi Munos
42
156
0
15 Dec 2015
Online Markov decision processes with policy iteration
Online Markov decision processes with policy iteration
Yao Ma
Huatian Zhang
Masashi Sugiyama
OffRL
26
3
0
15 Oct 2015
Solving Games with Functional Regret Estimation
Solving Games with Functional Regret Estimation
Kevin Waugh
Dustin Morrill
J. Andrew Bagnell
Michael Bowling
OffRL
34
58
0
28 Nov 2014
Online Learning in Markov Decision Processes with Adversarially Chosen
  Transition Probability Distributions
Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions
Yasin Abbasi-Yadkori
Peter L. Bartlett
Csaba Szepesvári
62
86
0
12 Mar 2013
No-Regret Learning in Extensive-Form Games with Imperfect Recall
No-Regret Learning in Extensive-Form Games with Imperfect Recall
Marc Lanctot
Richard G. Gibson
Neil Burch
Martin A. Zinkevich
Michael Bowling
OffRL
57
81
0
03 May 2012
A Reduction of Imitation Learning and Structured Prediction to No-Regret
  Online Learning
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
Stéphane Ross
Geoffrey J. Gordon
J. Andrew Bagnell
OffRL
152
3,196
0
02 Nov 2010
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