A continuous-time stochastic process is called a semi-Markov process or 'Markov renewal process' if the embedded jump chain (the discrete process registering what values the process takes) is a Markov chain, and where the holding times (time between jumps) are random variables with any distribution, whose distribution function may depend on the two states between which the move is made. A semi-Markov process where all the holding times are exponentially distributed is called a continuous time Markov chain/process

George Yin has written:

'Continuous-time Markov chains and applications' -- subject(s): Perturbation (Mathematics), Markov processes

Melvin Leroy Ott has written:

'Optimal policies in continuous Markov decision chains' -- subject(s): Markov processes

What is a continuous process

Communication is not an art or event at an instance of time rather it is a continuous process, incorporating various events and activities that are inter-related and inter-dependent.