An In-depth Look Into Q-learning’s Role In Reinforcement Learning

This article explores the versatility and effectiveness of Q-learning, a reinforcement learning algorithm that has become a powerhouse in the field of artificial intelligence and machine learning. It delves into the core concepts of Q-learning and its applications in single-agent and multi-agent scenarios, including deep Q-learning, hierarchical Q-learning, and modular Q-learning. The article also discusses the challenges and advancements in Q-learning, such as storage limitations and the fusion of deep learning and double Q-learning.