Synonyms
A stochastic process in which the conditional probability distribution of future states of the process, given the present state and all past states, depends only upon the present state. A process with this property may be called Markovian. The best known Markovian processes are Markov chains, also known as Markov Models, which are discrete-time series of states with transition probabilities. Markov chains are named after Andrey Markov (1865–1922), who introduced several significant new notions to the concept of stochastic processes. Brownian motion is another well-known phenomenon that, to close approximation, is a Markov process.
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Recommended Reading
Meyn SP, Tweedie RL (1993) Markov chains and stochastic stability. Springer, London
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(2017). Markov Process. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_516
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