A collection of frequently asked questions in Reinforcement Learning.


Reinforcement learning is complex subject and innocuous sounding questions can have complicated answers. I present some of most frequently asked questions below.

Simplifying RL Problems and Solutions

Oct 2020

Simplifying RL Problems You noted that many industrial applications could be solved with something as simple as tabular Q-learning. I was wondering if you could elaborate on that with some examples? If you’re talking about “many problems can be solved with simple algorithms”, then yes, there are many problems with low hanging fruit, that can be solved with simple algorithms. This comes down to a trade off between business value and technical difficulty.

RL Book and Topic Recommendations

Aug 2020

Multi-Agent Reinforcement Learning I’d like to learn more about the interplay between Reinforcement Learning and Multi-Agent Systems. Can you suggest some study resources such as books and scientific articles from where I can start learning? Multi-agent reinforcement learning (MARL) is a hot topic. This is because in the future, multiple agents are more likely to be able to solve a problem faster and better than they could alone. But the problem is that it makes the problem highly non-stationary.