What is Reinforcement learning??

In this blog, we will understand reinforcement learning in the simplest way.

Reinforcement Learning

During childhood, children go through a developmental phase in which they explore the world around them and learn about the rules that govern their behavior.

During this time, either children align with parental expectations or they don’t follow their rules. In response to such actions, parents may either punish them or reward them. when children meet the expectations set by their parents, they are rewarded with positive reinforcement but when they act wrong they get punished.

In the scenario of machine learning, reinforcement learning is the same. If the machine can take a good decision, it is rewarded; otherwise, it is punished. This is the way it learns.

In technical terms, this is a type of machine learning approach where an agent learns to make decisions by interacting with an environment. It receives feedback in the form of penalties and rewards, just like a child experiences consequences for their actions. Machine learns by taking sequential decisions.

To know two other types of Supervised learning, Unsupervised learning.

Here are some key terms related to Reinforcement Learning:

1. Agent: The entity or system that is making decisions within an environment. It’s the learner or decision-maker in the RL process.
2. Environment: The external system or context in which the agent operates and makes decisions. It can be real or simulated.
3. Action: The set of possible moves or decisions that an agent can make in a given state. Actions lead to transitions from one state to another.
4. Reward: A numerical value that the environment provides to the agent as feedback after the agent takes a particular action in a specific state. The reward indicates the immediate benefit or cost of the action

In the given scenario, the child acts as the agent. The environment presents two options: books and TV. The child’s actions, which involve selecting one option between books and TV, may result in either a reward or a punishment.

Reinforcement learning is a powerful paradigm that has been successfully applied in various fields, allowing machines to learn and improve through interaction with their environments, much like how children learn and grow through their experiences and interactions with the world around them.

Give it :👏👏👏👏:
If you found this guide helpful , why not show some love? Give it a Clap 👏, and if you have questions or topics you’d like to explore further, drop a comment 💬 below 👇. If you appreciate my hard work please follow me. That is the only way I can continue my passion.