Through simulation experiments using our approaches of Reinforcement Learning and Boolean Programming, we obtain good results in finding solutions for Optimal Stopping in American Options Pricing.

About L. Ai, et al., ‘Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models’, 2024, arXiv.

About The official repository of "Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models".

The Boolean complexity of a propositional concept is the length of the shortest Boolean formula logically equivalent to the concept, usually expressed in terms of the number of literals (positive ...

The use of decision tables as a tool in systems analysis and for program specification is now becoming accepted. Rules on redundancy, contradiction, and completeness for limited entry tables were ...

ABSTRACT: Generalized algorithms for solving problems of discrete, integer, and Boolean programming are discussed. These algorithms are associated with the method of normalized functions and are based ...

Benhamou, F. and Older, W. (1997) Applying Interval Arithmetlc to Real, Integer and Boolean Constraints. Journal of Logic Programming, 32, 1-24.