Artificial Intelligence, Reinforcement Learning, Machine Learning, Neural Networks, Markov Chains.
can be interpreted into a state transition matrix. Each row denotes the transition probability from any current state to the possible preceding states. MARKOV PROCESSES AND CHAINS These are essentially random sequences of states that contain the Markov property. All Markov chains are tuples <S, P>