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A Deep Reinforcement Learning Approach for Finding Non-Exploitable
  Strategies in Two-Player Atari Games
v1v2v3 (latest)

A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games

18 July 2022
Zihan Ding
DiJia Su
Qinghua Liu
Chi Jin
ArXiv (abs)PDFHTML

Papers citing "A Deep Reinforcement Learning Approach for Finding Non-Exploitable Strategies in Two-Player Atari Games"

2 / 2 papers shown
FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement
  Learning
FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
Wenzhe Li
Zihan Ding
Seth Karten
Chi Jin
345
9
0
04 Jun 2024
Zero-Sum Positional Differential Games as a Framework for Robust
  Reinforcement Learning: Deep Q-Learning Approach
Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning ApproachInternational Conference on Machine Learning (ICML), 2024
Anton Plaksin
Vitaly Kalev
217
1
0
03 May 2024
1