What is Reinforcement Learning?
Reinforcement learning is a machine learning approach that involves an agent learning how to interact with an environment to maximize its cumulative rewards. Unlike supervised and unsupervised learning, reinforcement learning focuses on learning through trial and error, where the agent takes actions in an environment and receives feedback in the form of rewards or penalties.In reinforcement learning, the agent learns to make decisions based on a sequence of observations and rewards. The agent takes actions in the environment, and based on the outcome of those actions, it receives feedback in the form of positive or negative rewards. The goal of the agent is to learn an optimal policy, a strategy for selecting actions, that maximizes the long-term cumulative rewards.Related terms
Not to be confused with:
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