Foundations of Reinforcement Learning and Interactive Decision Making

• URL: http://arxiv.org/abs/2312.16730v1
• Date: Wed, 27 Dec 2023 21:58:45 GMT
• Title: Foundations of Reinforcement Learning and Interactive Decision Making
• Authors: Dylan J. Foster and Alexander Rakhlin
• Abstract summary: We present a unifying framework for addressing the exploration-exploitation dilemma using frequentist and Bayesian approaches. Special attention is paid to function approximation and flexible model classes such as neural networks.
• Score: 81.76863968810423
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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