Reinforcement learning

Reinforcement learning is a field that has resurfaced recently, and it has become more popular in the fields of control, finding the solutions to games and situational problems, where a number of steps have to be implemented to solve a problem.

A formal definition of reinforcement learning is as follows:

"Reinforcement learning is the problem faced by an agent that must learn behavior through trial-and-error interactions with a dynamic environment.” (Kaelbling et al. 1996).

In order to have a reference frame for the type of problem we want to solve, we will start by going back to a mathematical concept developed in the 1950s, called the Markov decision process.

Markov decision process

Before explaining reinforcement learning techniques, we will explain the type of problem we will attack with them.

When talking about reinforcement learning, we want to optimize the problem of a Markov decision process. It consists of a mathematical model that aids decision making in situations...