Online Convex Optimization for Sequential Decision Processes and Extensive-Form Games

national conference on artificial intelligence, 2019.

Cited by: 25|Bibtex|Views47
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Regret minimization is a powerful tool for solving large-scale extensive-form games. State-of-the-art methods rely on minimizing regret locally at each decision point. In this work we derive a new framework for regret minimization on sequential decision problems and extensive-form games with general compact convex sets at each decision po...More

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