Rethinking formal models of partially observable multiagent decision making

DOI10.1016/j.artint.2021.103645OpenAlexW3215530464MaRDI QIDQ2667825

Vojtěch Kovařík, Michael Bowling, Neil Burch, Viliam Lisý, Martin J. Schmid

Publication date: 2 March 2022

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1906.11110

zbMATH Keywords

decompositionpublic informationextensive form gameimperfect information gamemultiagent reinforcement learningpartially-observable stochastic game

Mathematics Subject Classification ID

Artificial intelligence (68Txx)

Related Items (1)

Value functions for depth-limited solving in zero-sum imperfect-information games

Uses Software

• DeepStack
• Libratus
• Pluribus
• Agent57

Cites Work

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• Existence of Nash equilibria in finite extensive form games with imperfect recall: A counterexample
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• Timeability of Extensive-Form Games
• Multiagent Systems
• A Simple Adaptive Procedure Leading to Correlated Equilibrium
• DeepStack: Expert-level artificial intelligence in heads-up no-limit poker
• Superhuman AI for multiplayer poker
• Decentralized Stochastic Control with Partial History Sharing: A Common Information Approach
• Algorithmic Game Theory

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