This year, we have seen all the hype around AI Deep Learning. With recent innovations, deep learning demonstrated its usefulness in performing tasks such as image recognition, voice recognition, price forecasting, across many industries. It’s easy to overestimate deep learning’s capabilities and pretend it’s the magic bullet that will allow AI to obtain General Intelligence. In truth, we are still far away from that. However, deep learning has a relatively unknown partner: Reinforcement Learning. As AI researchers venture into the areas of Meta-Learning, attempting to give AI learning capabilities, in conjunction with deep learning, reinforcement learning will play a crucial role.

What is Reinforcement Learning?

Imagine a child who is learning by interacting with their environment. Each touch will generate a sensation that can result in a reward. For instance, the pleasant smell of the flower will entice the child to want to smell the flower again; the pain from a prick of the flower’s stem will alert the child who will refrain from touching the stem again.