Probabilistic Programming - Tapa blanda

Reseña del editor

Mathematical programming involves the planning of industrial, administrative, and economic activities. Its emerging subfield, probabilistic programming, approaches objectives in terms of probability. Several disciplines ? including knowledge representation, reasoning about uncertainty, data mining, and machine learning ? are increasingly adopting the methods of probabilistic programming. For 50 years, author Steven Vajda played an important role in the development of mathematical programming and operations research. Although he wrote this book in 1972, its discussions of theoretical foundations are not phrased in terms of specific programming languages, and it remains an undated survey of an increasingly vital subject.
The three-part treatment begins with stochastic programming and advances to explorations of decision problems and chance constraints. Appendixes cover linear and stochastic programming in various fields. This text is geared toward graduate students and researchers in the fields of computer science, mathematics, and industrial engineering.