Review:
Markov Decision Process
overall review score: 4.2
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score is between 0 and 5
A Markov Decision Process (MDP) is a mathematical framework used to model decision-making in situations where outcomes are partly random and partly under control.
Key Features
- State space
- Action space
- Transition probabilities
- Rewards
Pros
- Provides a formal framework for decision-making under uncertainty
- Used in various fields such as AI, robotics, and economics
Cons
- Can be computationally intensive for large state spaces