What are the different types of Markov models?

What are the different types of Markov models?

There are several types of Markov models, including Markov Chains, Hidden Markov Models (HMM), and Markov Decision Processes (MDP). Would you like to know more about a specific type?

Can you explain Hidden Markov Models?

Sure! Hidden Markov Models are statistical models where the system is assumed to be a Markov process with unobservable states. They are widely used in areas like speech recognition and bioinformatics.

What about Markov Decision Processes?

Markov Decision Processes are used for modeling decision-making situations where outcomes are partly random and partly under the control of a decision maker. They are essential in reinforcement learning.

How do these models differ from each other?

The main difference lies in their applications and the nature of the states. Markov Chains deal with observable states, HMMs with hidden states, and MDPs incorporate decision-making.