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Uncertainty, Probability & Markov Chains, image, image - Coggle Diagram
Uncertainty, Probability & Markov Chains
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Rational Decision Making
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Uncertainty complicates even simple decisions (e.g., timing to airport)
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Probability Theory
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Application
Example: Believing there's 0.8 probability of a cavity doesn't mean it exists or not just reflects current belief
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Definition: Probability measures how likely an event is, on a scale from 0 to 1.
Utility Theory
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Example: Choosing between waiting 4 hours at the airport (less utility) vs. risking missing a flight (even lower utility).
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Decision Theory
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Example: Based on probability of traffic and personal preference for not missing flights, the agent chooses when to leave.
Markov Model
Definition
Markov property: Future state depends only on the present, not the past
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Markov Chain
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Components
Set of States: e.g., Rainy, Sunny
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