A Tutorial Introduction to Reinforcement Learning

2023-04-03 · Mathukumalli Vidyasagar

In this paper, we present a brief survey of Reinforcement Learning (RL), with particular emphasis on Stochastic Approximation (SA) as a unifying theme. The scope of the paper includes Markov Reward Processes, Markov Decision Processes, Stochastic Approximation algorithms, and widely used algorithms such as Temporal Difference Learning and $Q$-learning.

📄 PDF Abstract BibTeX arXiv:2304.00803

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