Explain the concept of reinforcement learning in AI.
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Reinforcement learning is a type of machine learning where an agent learns to make decisions by interacting with an environment. The agent receives feedback in the form of rewards or penalties based on its actions, and its goal is to maximize cumulative reward over time through trial and error.
Reinforcement learning is a type of machine learning where an agent learns to make decisions by interacting with an environment.
The agent receives feedback in the form of rewards or penalties based on its actions, and its goal is to maximize the cumulative reward over time.
Through trial and error, the agent learns which actions lead to the most favorable outcomes.
Reinforcement learning is inspired by how humans and animals learn from experience, and it’s
used in various applications, including game playing, robotics, and autonomous driving.