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components
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#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 .
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 .
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