The AIFI Newsletter: New Paper - "Reinforcement Learning: A Historical and Mathematical Overview (1950-2024)"
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Date Written: September 21, 2024
Abstract
This paper provides an exhaustive overview of the evolution of Reinforcement Learning (RL) from its inception in the 1950s to the cutting-edge developments up to 2024. Emphasis is placed on the mathematical foundations and theoretical advancements that have shaped the field. We delve deeply into the principles of dynamic programming, temporal difference learning, and the integration of deep learning techniques. By tracing the chronological progression of RL, we aim to elucidate how foundational concepts have evolved into sophisticated algorithms that address complex, real-world problems. This comprehensive examination is intended for readers with a solid mathematical background seeking an in-depth understanding of RL's development.
Keywords: rl, reinforcement learning, artificial intelligence