What Is Reinforcement Learning

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What is Reinforcement learning, and what is reinforcement learning in neural networks? What are the four types of reinforcement? And give an example of reinforcement learning, which can help in better understanding.

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What Is Reinforcement Learning

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Reinforcement learning is an area of machine learning. It is all about taking suitable actions that can minimize reward. It is finding the shortest path to reach your destination. Reinforcement learning solves the difficult problem of comparing and connecting critical steps. Reinforcement learning algorithms can be presumed to deliver more solid and numerous enigmatic steps.

Reinforcement learning like extensive neural networks is one such approach relying on sampling to obtain knowledge from data.

The four types of reinforcement schedules are:

  • Fixed-Ratio (FR) Schedule.
  • Fixed-Interval (FI) Schedule.
  • Variable-Ratio (VR) Schedule.
  • Variable-Interval (VI) Schedule.

Example: we have a robot and a reward that is diamond. The robot is supposed to find the best possible path to reach the prize.

Each right step rewards the robot, and each wrong step subtracts the reward. This is just as similar as Mario in which Mario had to reach its destination bypassing all the hurdles without touching any of the obstructions.

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