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Bookmark or Share- Introduction to Reinforcement Learning | SpringerLinkIn this chapter, we introduce the fundamentals of classical reinforcement learning and provide a general overview of deep reinforcement learning. We first start with the basic definitions and concepts of reinforcement learning, including the agent, environment,...
- What is reinforcement learning? - IBMIn reinforcement learning, an autonomous agent learns to perform a task by trial and error in the absence of any guidance from a human user. 1 It particularly addresses sequential decision-making problems in uncertain environments, and shows promise in artificial intelligence development.
- Reinforcement learning - GeeksforGeeksReinforcement Learning (RL) is a branch of machine learning focused on making decisions to maximize cumulative rewards in a given situation. Unlike supervised learning, which relies on a training dataset with predefined answers, RL involves learning through experience.
- What is Reinforcement Learning? - Reinforcement Learning Explained - AWSReinforcement learning (RL) is a machine learning (ML) technique that trains software to make decisions to achieve the most optimal results. It mimics the trial-and-error learning process that humans use to achieve their goals.
- Lecture 14: Reinforcement Learning - Stanford UniversityOverview. What is Reinforcement Learning? Markov Decision Processes. Q-Learning. Policy Gradients. Reinforcement Learning.
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