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Uncertainty - Coggle Diagram
Uncertainty
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Hidden Markov Model
HMMs identify patterns in sequential data, assuming each observation depends on an unobservable state.
HMMs simplify complex systems using the Markov property, where future states depend only on the current state.
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Rational Decision
A rational decision in AI is a choice made by an AI system that maximizes the expected utility or benefit, given the available information and predefined goals or objectives.
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Probability Theory
The study of random phenomena is the focus of the mathematical field of probability theory. A random variable, or a quantity whose result is uncertain, is the fundamental object of probability theory.
Decision theory
The development of algorithms that make predictions or make decisions in the face of ambiguity is made possible thanks in large part to Decision Theory, which improves the efficacy and efficiency of AI systems.
Markov Chains
Are comparable to the sequences that FSMs prescribe. EXCEPT that rather than a clear input/output causation, there is a probability linked to the subsequent sequence that needs to be followed.
Chaos theory
Chaos theory explains the behavior of dynamic systems like weather, which are extremely sensitive to initial conditions.