A robot who updates its beliefs using Bayesian reasoning has just obtained measurement z from pointing its sensor array at a door. It would like to determine whether the door is open (P(open|z)) before driving forward. The prior probability of P (open) = 0.3 and P (closed) = 0.7 Your sensor model indicates that the likelihood of seeing that observation is P(z|open) = 0.6 and P (z|closed) = 0.3. Calculate the posterior P (open|z).

A robot who updates its beliefs using Bayesian reasoning has just obtained measurement z from pointing its sensor array at a door. It would like to determine whether the door is open (P(open|z)) before driving forward. The prior probability of P (open) = 0.3 and P (closed) = 0.7 Your sensor model indicates that the likelihood of seeing that observation is P(z|open) = 0.6 and P (z|closed) = 0.3. Calculate the posterior P (open|z).

Operations Research : Applications and Algorithms

4th Edition

ISBN:9780534380588

Author:Wayne L. Winston

Publisher:Wayne L. Winston

Chapter17: Markov Chains

Section17.6: Absorbing Chains

Problem 7P

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