On Estimation and Optimization of Probability

In this paper, we develop a general approach for probabilistic estimation and optimization. An explicit formula is derived for controlling the reliability of probabilistic estimation based on a mixed criterion of absolute and relative errors. By employing the Chernoff bound and the concept of sampling, the minimization of a probabilistic function is transformed into an optimization problem amenable for gradient descendent algorithms.