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Uncertainty - Coggle Diagram
Uncertainty
Probability Theory
Summarizes uncertainty from laziness and ignorance
Probability ranges from 0 to 1
Importance of state knowledge
Degree of belief based on knowledge
Problem-Solving and Belief State
Drawback: excessive reliance on logic
Logical agents track belief state (representation of all possible world states)
Contingency planning
Stochastic Processes
Collection of random variables
Represents system evolution over time
Applications: statistical models of real world
Markov Chains
Transition between states with associated probabilities
Memoryless (depends only on current state)
Examples
, blood pressure
weather
, stock market
Utility Theory
Every state has a degree of usefulness
Preferences regarding outcomes
Decision Theory
Combines probability theory and utility theory
Rational agents choose actions yielding highest expected utility
Markov Chain Monte Carlo (MCMC)
Analysis technique using random sampling
Analysis technique using random sampling
Hidden Markov Models (HMM)
Simplifies models
Applications
DNA sequencing
genetic drift
page ranking
what is Uncertainty
Epistemic circumstances containing incomplete or unknown knowledge are referred to as uncertain.