Learning Probably Approximately Correct Maximin Strategies in Simulation-Based Games with Infinite Strategy Spaces

18 November 2019

Papers citing "Learning Probably Approximately Correct Maximin Strategies in Simulation-Based Games with Infinite Strategy Spaces"

10 / 10 papers shown

Title
Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games Chun Kai Ling Fei Fang J. Zico Kolter 43 29 0 11 Mar 2019
Competitive Bridge Bidding with Deep Neural Networks Jiang Rong Tao Qin Bo An 23 22 0 03 Mar 2019
Bandit learning in concave $N$ -person games Mario Bravo David S. Leslie P. Mertikopoulos 34 122 0 03 Oct 2018
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization Bryan Wilder B. Dilkina Milind Tambe OffRL AI4CE 62 297 0 14 Sep 2018
What game are we playing? End-to-end learning in normal and extensive form games Chun Kai Ling Fei Fang J. Zico Kolter 74 84 0 07 May 2018
A Generalised Method for Empirical Game Theoretic Analysis K. Tuyls Julien Perolat Marc Lanctot Joel Z Leibo T. Graepel 36 57 0 16 Mar 2018
Safe and Nested Subgame Solving for Imperfect-Information Games Noam Brown Tuomas Sandholm 76 182 0 08 May 2017
On Kernelized Multi-armed Bandits Sayak Ray Chowdhury Aditya Gopalan 109 460 0 03 Apr 2017
Maximin Action Identification: A New Bandit Framework for Games Aurélien Garivier E. Kaufmann Wouter M. Koolen 63 29 0 15 Feb 2016
On the Complexity of Best Arm Identification in Multi-Armed Bandit Models E. Kaufmann Olivier Cappé Aurélien Garivier 172 1,025 0 16 Jul 2014