Real Time Estimation of Bayesian Networks
This addresses the need for guaranteed response times in real-time Bayesian network evaluation, though it appears incremental as it builds on existing approximation techniques.
The paper tackled the problem of real-time evaluation of Bayesian networks when exact solutions are infeasible, showing that nontraditional methods using estimators from an archive of trial solutions and genetic search provide an approximate solution that is considerably superior to traditional Monte Carlo simulation methods.
For real time evaluation of a Bayesian network when there is not sufficient time to obtain an exact solution, a guaranteed response time, approximate solution is required. It is shown that nontraditional methods utilizing estimators based on an archive of trial solutions and genetic search can provide an approximate solution that is considerably superior to the traditional Monte Carlo simulation methods.