Title :
How to combine stochastic programming and mathematical theory of programming
Author_Institution :
Department of Computers and Informatics, Faculty of Electrical Engineering and Informatics, Ko?ice, Slovak Republic
Abstract :
In the contribution presented we deal with one method of stochastic programming - probabilistic programming. Probabilistic programming is a method of stochastic programming in which the probabilities of the values of the variables are of interest. Our approach is that scientific problem solving we can construct in logical reasoning over some mathematical theories. In this approach we deal with category theory for construction of type theory and of the logical system. Then we formulate the logical theory to enclose the solution of the problem. These steps we show at well-known examples: the random number generator, the Blackjack game and the Monty Hall problem.
Keywords :
"Mathematical programming","Stochastic processes","Data structures","Informatics","Problem-solving","Logic programming","Input variables","Uncertainty","Probability distribution","Random number generation"
Conference_Titel :
Applied Machine Intelligence and Informatics, 2008. SAMI 2008. 6th International Symposium on
Print_ISBN :
978-1-4244-2105-3
DOI :
10.1109/SAMI.2008.4469181