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  • title: R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games
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            R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games
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            R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games

            Jul 12, 2020

            Sprecher:innen

            ZD

            Zhongxiang Dai

            Sprecher:in · 0 Follower:innen

            YC

            Yizhou Chen

            Sprecher:in · 0 Follower:innen

            BK

            Bryan Kian

            Sprecher:in · 2 Follower:innen

            Über

            This paper presents a recursive reasoning formalism of Bayesian optimization (BO) to model the reasoning process in the interactions between boundedly rational, self-interested agents with unknown, complex, and costly-to-evaluate payoff functions in repeated games, which we call Recursive Reasoning-Based BO (R2-B2). Our R2-B2 algorithm is general in that it does not constrain the relationship among the payoff functions of different agents and can thus be applied to various types of games such as…

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            I2
            I2

            ICML 2020

            Konto · 210 Follower:innen

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            App- und Spieleentwicklung

            Kategorie · 954 Präsentationen

            KI und Datenwissenschaft

            Kategorie · 10,8k Präsentationen

            Über ICML 2020

            The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

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