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Markov Decision Processes (MDP)

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Primary software used Jupyter Notebook
Course Markov Decision Processes (MDP)
Primary subject AI & ML
Secondary subject Machine Learning
Level Intermediate
Last updated November 11, 2024
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Markov Decision Processes (MDP)

A Markov Decision Process (MDP) is a mathematical framework used to model decision-making in situations where outcomes are partly random and partly under the control of a decision maker. It consists of states, actions, transition probabilities, and rewards, allowing the formulation of optimal strategies to maximize expected cumulative rewards over time.

For this tutorial you need to have installed Python, Jupyter notebooks, and some common libraries including Scikit Learn. Please see the following tutorial for more information.

Jupyter Notebook Installation & Overview

Download the Jupyter notebook here to follow along with the tutorial.

Download MDP_PYscript_01
application/zip (ZIP, 63 KB)
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