By Ramon López de Mántaras; David L Poole
Read or Download Uncertainty in artificial intelligence : proceedings of the Tenth Conference (1994) : July 29-31, 1994 PDF
Similar nonfiction_12 books
The Mysterious Island tells the fascinating tale of 5 americans stranded on an uncharted island within the South Pacific. in the course of the American Civil conflict, Richmond, Virginia was once the capital of the accomplice States of the US. 5 northern prisoners of struggle choose to get away Richmond in a slightly strange method - by way of hijacking a balloon.
- Topological States on Interfaces Protected by Symmetry
- High-Frequency Magnetic Components, Second Edition
- Curriculum and Assessment. Some Policy Issues
- Robotic Surgery: Current Applications and New Trends
Extra info for Uncertainty in artificial intelligence : proceedings of the Tenth Conference (1994) : July 29-31, 1994
But it does not seem appropriate for her to do eitl1er; rather we would like to he able to generate a degree of belief in Cardinal(b) that takes into account the birdwatcher's degree of belief in Red( b ) . 8. 1 . A s another example, suppose we have reason to believe that two sensors are independent. For simplicity, suppose the sensors measure temperature, and report it to be either high, h, or low, /. We can imagine t11ree unary predicates: SJ ( i: ) , indicating that sensor 1 reports the value x; S2(x), a simi lar predicate for sensor 2; and A ctual( x ) , indicating that the actual temperature is x.
The application of equation (10) to approximate Var(g(0)jX) and Cov(g1 (0 ) , g 2 (0) jX) using the ex pressions (omitting 0 ) : .. 10 1 % error log scale Beta Posterior - Example �ost . 01 0 . ---'---< 10 20 3 0 40 50 60 70 80 90 100 n En ( 9192 I X) - En (g 1 ! X) ( l + O( n - 2 ) ) ( 14) and Figure 2 : Errors in Approximations for E(O I X) . ve ly, 0' 1 = p + +p+a +b a -2 . 0)7r(0) is always nonnegative) . This case can be addressed by at least two alternative approaches. The first one considers setting h(e, s) = exp(s g(0)) (that is al ways nonnegative) , computing Laplace's approxima tion for E( h ( e)) , the moment generating function ( mgf ) for g(0), fixing s at a convenient value where the mgf is defined, and then using the approximation & E( ,s)) E(g(0)) = ls= O (the definition of expecta tion from a mgf of a random variable).
Suppose that we want to compute the marginal posterior probability 7r(Bu IX) us ing Laplace 's method. In this example nep , neq L (Xj0) 7r (0) An approximation for equation ( 16) can be easily found for Bp = k using two alternative approaches. The first approach considers the use of Laplace's method to approximate both the integral part in equa tion ( 16) and the constant c defined in equation ( 1 7 ) . In the second approach the constant c i s approximated by an external procedure, usually numerical integra tion, that is very effective in low dimensions (and fre quently p = 1 or 2), according to Naylor and Smith  .
Uncertainty in artificial intelligence : proceedings of the Tenth Conference (1994) : July 29-31, 1994 by Ramon López de Mántaras; David L Poole