Foundations of Reinforcement Learning and Interactive Decision Making

Dylan J. Foster; Alexander Rakhlin

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arXiv · 2312.16730

Foundations of Reinforcement Learning and Interactive Decision Making

Dylan J. Foster·Alexander Rakhlin

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Abstract

These lecture notes give a statistical perspective on the foundations of reinforcement learning and interactive decision making. We present a unifying framework for addressing the exploration-exploitation dilemma using frequentist and Bayesian approaches, with connections and parallels between supervised learning/estimation and decision making as an overarching theme. Special attention is paid to function approximation and flexible model classes such as neural networks. Topics covered include multi-armed and contextual bandits, structured bandits, and reinforcement learning with high-dimensional feedback.

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Dylan J. Foster, Alexander Rakhlin. 2023-12-27. Foundations of Reinforcement Learning and Interactive Decision Making. https://arxiv.org/abs/2312.16730

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