markov chains are very simple at their core (e.g. simple version could be: take the probability of the next word given the known probabilities of words that fol

markov chains are very simple at their core (e.g. simple version could be: take the probability of the next word given the known probabilities of words that follow the previous word) it can be implemented in a few lines of code, that's the beauty of it: https://github.com/justindomingue/markov_chains/blob/master/lib/markov_chains/dictionary.rb https://github.com/justindomingue/markov_chains/blob/master/... obviously then you could take the previous n words into account, tweak the starting word, add randomness, etc. now replace "word" with "state" and "probability(next state | previous state)" to edges of a graph: https://static1.squarespace.com/static/54e50c15e4b058fc6806d068/t/5650d16ee4b033f56d20ae6b/1459882428797/markov+chain+graph+all.png?format=1500w https://static1.squarespace.com/static/54e50c15e4b058fc6806d... and you got a generic markov chain :) footnotes: p(A | B) is probability of A given B, e.g. p(rain | clouds) > p(rain | sun) :)