What is Reinforcement Learning Model-Free vs. Model-Based?
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Reinforcement Learning, Model-Free and Model-Based approaches are two different paradigms. Model-Free methods learn directly from interactions with the environment without explicitly building a model of the environment. They focus on learning the optimal policy or value function. Model-Based methods, on the other hand, build an explicit model of the environment dynamics and use it to plan and make decisions. They combine model learning and model-based control to find the optimal policy.
