A Data Science Central Community
Summary: Reinforcement Learning (RL) is likely to be the next big push in artificial intelligence. It’s the core technique for robotics, smart IoT, game play, and many other emerging areas. But the concept of modeling in RL is very different from our statistical techniques and deep learning. In this two part series we’ll take a look at the basics of RL models, how they’re built and used. In the next part, we’ll address some of the complexities that make development a challenge.
Now that we have pretty much conquered speech, text, and image processing with deep neural nets, it’s time to turn our attention to what comes next. It’s likely that the next most important area of development for AI will be reinforcement learning (RL).
RL systems are getting a lot of play in the press from self-driving cars and winning at Go but the reality is that they are not quite yet ready for commercialization. We wrote about the readiness of the various techniques behind AI earlier and published this chart.