An Introduction to Reinforcement Learning – III :: Dynamic Programming Applications to the OpenAI Gym

Welcome back to my series of articles on Reinforcement Learning, where I stumble through and try and understand RL, and hopefully convey some useful knowledge along the way. In the first article, I talked about the basic terminology and concepts and ultimately introduced Markov Decision Processes (MDPs). In the second article in the series, the […]

Read More An Introduction to Reinforcement Learning – III :: Dynamic Programming Applications to the OpenAI Gym

An Introduction to Reinforcement Learning – I :: Markov Decision Processes

1. Introduction The best way to understand something is to try and explain it. And if you keep getting better every time you try to explain it, well, that’s roughly the gist of what Reinforcement Learning (RL) is about.  Given how different RL is from Supervised or Unsupervised Learning, I figured that the best strategy is […]

Read More An Introduction to Reinforcement Learning – I :: Markov Decision Processes