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Deep Fictitious Play for Stochastic Differential Games
v1v2v3 (latest)

Deep Fictitious Play for Stochastic Differential Games

22 March 2019
Ruimeng Hu
ArXiv (abs)PDFHTML

Papers citing "Deep Fictitious Play for Stochastic Differential Games"

13 / 13 papers shown
Title
Convergence of Deep Fictitious Play for Stochastic Differential Games
Convergence of Deep Fictitious Play for Stochastic Differential Games
Jiequn Han
Ruimeng Hu
Jihao Long
45
20
0
12 Aug 2020
Deep Fictitious Play for Finding Markovian Nash Equilibrium in
  Multi-Agent Games
Deep Fictitious Play for Finding Markovian Nash Equilibrium in Multi-Agent Games
Jiequn Han
Ruimeng Hu
55
44
0
04 Dec 2019
On the Convergence of Adam and Beyond
On the Convergence of Adam and Beyond
Sashank J. Reddi
Satyen Kale
Surinder Kumar
99
2,499
0
19 Apr 2019
Deep Learning for Ranking Response Surfaces with Applications to Optimal
  Stopping Problems
Deep Learning for Ranking Response Surfaces with Applications to Optimal Stopping Problems
Ruimeng Hu
OOD
49
12
0
11 Jan 2019
Deep neural networks algorithms for stochastic control problems on
  finite horizon: numerical applications
Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications
Achref Bachouch
Côme Huré
N. Langrené
H. Pham
74
87
0
13 Dec 2018
Convergence of the Deep BSDE Method for Coupled FBSDEs
Convergence of the Deep BSDE Method for Coupled FBSDEs
Jiequn Han
Jihao Long
59
159
0
03 Nov 2018
Decentralised Learning in Systems with Many, Many Strategic Agents
Decentralised Learning in Systems with Many, Many Strategic Agents
D. Mguni
Joel Jennings
Enrique Munoz de Cote
57
63
0
13 Mar 2018
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
Marc Lanctot
V. Zambaldi
A. Gruslys
Angeliki Lazaridou
K. Tuyls
Julien Perolat
David Silver
T. Graepel
112
636
0
02 Nov 2017
Deep learning-based numerical methods for high-dimensional parabolic
  partial differential equations and backward stochastic differential equations
Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations
Weinan E
Jiequn Han
Arnulf Jentzen
125
798
0
15 Jun 2017
Deep Learning Approximation for Stochastic Control Problems
Deep Learning Approximation for Stochastic Control Problems
Jiequn Han
E. Weinan
BDL
53
195
0
02 Nov 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
53
399
0
03 Mar 2016
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
463
43,305
0
11 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.9K
150,115
0
22 Dec 2014
1