Markov Decision Process (Mdp)
A mathematical framework used for modeling decision-making in situations where outcomes are partly random and partly under the control of a decision-maker. MDPs extend Markov chains by adding actions and rewards, which introduce the concepts of choice and motivation, respectively.
Areas of application
- operations research
- artificial intelligence
- economics
- management science
- decision making
Example
Consider a company that wants to optimize its manufacturing process. The company can choose from different production strategies, each with its own set of actions (e.g., using different materials or machines) and rewards (e.g., increased productivity or reduced costs). By modeling the decision-making process as an MDP, the company can analyze the expected outcomes of each strategy and choose the one that maximizes its reward.