A Markov Chain is a mathematical system that undergoes transitions from one state to another, where the probability of transitioning from one state to another is dependent on the current state. This means that the future state of the system depends only on its current state, and not on any of its past states. This property, known as the "memoryless" property, makes Markov Chains particularly useful for modeling complex systems that exhibit random behavior.
She was asleep when he sat down in the plastic chair beside her. He didn’t know what to do. Markov chains didn’t cover this. There was no transition probability for how to sit with your dying daughter after eleven years of silence . markov chain norris
Because these sentences have a consistent structure and a finite vocabulary, they are the perfect "training data" for a basic Markov Chain text generator. How a "Markov Chain Norris" Generator Works A Markov Chain is a mathematical system that