Tag: Q-Learning Algorithm
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Mastering Q-Learning: A Step-by-Step Guide to Reinforcement Learning in Machine Learning
Introduction: What is Q-Learning? Q-Learning is a fundamental reinforcement learning algorithm that enables an agent to learn optimal actions in a given environment by maximizing rewards. It’s a model-free algorithm, meaning it doesn’t require prior knowledge of the environment’s dynamics. Instead, it learns from trial-and-error interactions, making it a powerful tool for decision-making problems. How… Read more
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Reinforcement Learning Algorithms: Key Concepts, Techniques, and Real-World Applications
Introduction to Reinforcement Learning (RL) Reinforcement Learning (RL) is a branch of machine learning where an agent learns to make decisions by interacting with its environment. Instead of relying on labeled data, RL focuses on learning through trial and error, guided by a reward system. The agent aims to maximize cumulative rewards by taking actions… Read more