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Understanding Markov Decision Processes by Anonymous LI2DAcv is a document available to read on EtoBox.
What is Understanding Markov Decision Processes about?
The document discusses Markov Decision Processes (MDPs), which provide a framework for sequential decision making in uncertain environments. An MDP is modeled as a 4-tuple of states, actions, transition probabilities, and rewards. Transition probabilities define the likelihood of moving between states based on actions. The goal is to find an optimal policy that maximizes expected rewards over time. MDPs can be used for problems involving uncertainty like robotics, resource allocation, and more. A policy map
- Author
- Anonymous LI2DAcv
- Language
- EN