How machines can teach themselves without human intervention

What is reinforcement learning?

Reinforcement learning basically uses the exact same thought process that our baby used above to allow machines to learn from their environment. Let’s take a look at the specifics of the process.

Why is reinforcement learning useful?

So at this point, we understand what reinforcement learning is useful, but why would anyone ever want to use it for their machines. Aren’t there already better and fancier methods out there? What’s the benefit of using reinforcement learning over one of those fancy neural network things?

Key Takeaways

  • In its most essential form, reinforcement learning is simple and is analogous to how humans learn.
  • Reinforcement learning involves an agent that takes actions in an environment. This environment can be anything that the agent needs to get good at.
  • The agent interprets which actions are good and bad based on the rewards it receives from the environment and the state of the environment.
  • Reinforcement learning is very powerful and is useful for tasks where a machine has to achieve a specific goal.

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I’m Adam, a 17 year old passionate in technologies like artificial intelligence/machine learning, blockchain, quantum computing, and much more.



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