chapter13 - Uncertainty CHAPTER 13 HASSAN KHOSRAVI...

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CHAPTER 13 HASSAN KHOSRAVI SPRING2011 Uncertainty
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Outline Uncertainty Probability Syntax and Semantics Inference Independence and Bayes' Rule
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In many cases, our knowledge of the world is incomplete (not enough information) or uncertain (sensors are unreliable). Often, rules about the domain are incomplete or even incorrect We have to act in spite of this! Drawing conclusions under uncertainty
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Example Goal: The agent wants to drive someone to air port to catch a flight Let action A t = leave for airport t minutes before flight Will A t get me there on time? Problems: 1. partial observability (road state, other drivers' plans, etc.) 2. noisy sensors (traffic reports) 3. uncertainty in action outcomes (flat tire, etc.) 4. immense complexity of modeling and predicting traffic Hence a purely logical approach either 1. risks falsehood: “ A 25 will get me there on time”, or 2. leads to conclusions that are too weak for decision making: A 25 will get me there on time if there's no accident on the bridge and it doesn't rain and my tires remain intact etc etc .” ( A 1440 might reasonably be said to get me there on time but I'd have to stay overnight in the airport …)
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Uncertainty in logical rules
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Probability First order logic fails with medical diagnosis laziness : failure to enumerate exceptions, qualifications, etc. Theoretical ignorance : lack of relevant facts, initial conditions, etc. Practical ignorance: Even if we know all the rules, a patience might not have done all the necessary tests. Probabilistic assertions summarize effects of Laziness Ignorance
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Degree of belief vs degree of truth Probability of 0.8 does not mean 80% true. A card is taken out of a deck of cards The probability of it being Ace of clubs The probability after seeing the card Being 0.8 intelligence is not probabilistic. It means on a scale of 0 to 1 you are 0.8 intelligence
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Methods for handling uncertainty Default or nonmonotonic logic: Assume my car does not have a flat tire Assume A 25 works unless contradicted by evidence Issues: What assumptions are reasonable? How to handle contradiction?
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Making decisions under uncertainty Suppose I believe the following: P(A 25 gets me there on time | …) = 0.04 P(A 90 gets me there on time | …) = 0.70 P(A 120 gets me there on time | …) = 0.95 P(A 1440 gets me there on time | …) = 0.9999 Which action to choose? Which one is rational? Depends on my
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This note was uploaded on 10/03/2011 for the course CMPT 320 taught by Professor Stevenpearce during the Winter '09 term at Simon Fraser.

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chapter13 - Uncertainty CHAPTER 13 HASSAN KHOSRAVI...

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