An Introduction to Reinforcement Learning

Reinforcement learning is a type of machine learning technique where a computer agent learns to perform a task through repeated trial and error interactions with a dynamic environment. This learning approach enables the agent to make a series of decisions that maximize a reward metric for the task without human intervention and without being explicitly programmed to achieve the task.

Want to know more about Introduction to Reinforcement Learning? Read the blog post at https://k21academy.com/aiml14 to learn more.

The blog post covers:
• What Is Reinforcement Learning (RL)?
• What is Policy Search?
• What is Learning?
• How Is RL Similar to Traditional Controls?
• RL Workflow Overview
• What is Environment?
• Model-Free RL Vs Model-Based RL

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