# Markov Chains Markov Chains are a type of **stochastic process** (a collection of random variables that evolves over time) that satisfy the **Markov property** (the future state $$n+1$$ only depends on the current state $$n$$, and not any of the past states). Markov chains are often used to model transitions between discrete states. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://cs70.bencuan.me/probability/markov-chains.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.