Markov decision processes (MDPs) and stochastic control constitute pivotal frameworks for modelling decision-making in systems subject to uncertainty. At their core, MDPs provide a structured means to ...

A Markov-modulated Poisson Process (MMPP) is a Poisson process that has its parameter controlled by a Markov process. These arrival processes are typical in communications modeling where time-varying ...

High-order Markov chain models extend the conventional framework by incorporating dependencies that span several previous states rather than solely the immediate past. This extension allows for a ...

There’s an odd little trick to how AI programs, including large language models such as ChatGPT, learn and make decisions. The oddest thing about it is that it can be traced to a Russian born in 1856.