Tag: Applications of reinforcement learning
Reinforcement Learning: Maximizing Rewards through Continuous Learning and Markov Decision Processes
Reinforcement learning (RL) is a subfield of machine learning that focuses on using reward functions to train agents to make decisions and actions in an environment that maximizes their cumulative reward over time. RL is one of the three main machine learning paradigms, along with supervised and unsupervised learning. There are two main types of…
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Dynamic Programming in Reinforcement Learning: Policy and Value Iteration
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