#Components of Markov Decision Process

States (S):

Represents all possible situations an agent can be in.

Example in #OpenfabricA I: The current status of a trading bot monitoring stock prices or a chatbot tracking user conversation flow.

Actions (A):

All possible actions the agent can take in each state.

Example: A recommendation engine choosing a product to suggest based on user preferences.

Transition Probabilities (P):

The probability of moving from one state .