Lecture on Reinforcement Learning and Agent Based Modeling

This lecture introduces Reinforcement Learning (RL) in the context of Agent-Based Modeling (ABM). It explores how RL can be used to train intelligent agents that operate within an ABM, making them adaptive and decision-driven rather than rule-based. To highlight practical applications, the lecture briefly examines the role of RL in crop management, demonstrating how learning agents can optimize agricultural practices.