Keras Reinforcement Learning Projects

Transition matrix

The study of time-homogeneous Markov chains (whose transition probabilities are independent of time) becomes particularly simple and effective using matrix representation. In particular, the formula expressed by the previous proposition becomes much more readable. The structure of a Markov chain is therefore completely represented by the following transition matrix:

The properties of transition probability matrices derive directly from the nature of the elements that compose them. In fact, by observing that the elements of the matrix are probabilities, they must have a value between 0 and 1. So, this is a positive matrix ...