In constraint programming one models a problem by stating constraints on acceptable solutions. The constraint model is then usually solved by interleaving backtracking search and ...
Local genetic algorithms have been designed with the aim of providing effective intensiļ¬cation. One of their most outstanding features is that they may help classical local searc...
In this paper, we develop a stochastic approximation method to solve a monotone estimation problem and use this method to enhance the empirical performance of the Q-learning algor...
: We initiate the study of local, sublinear time algorithms for finding vertices with extreme topological properties -- such as high degree or clustering coefficient -- in large so...
Quantum evolutionary algorithm (QEA) is proposed on the basis of the concept and principles of quantum computing, which is a classical metaheuristic algorithm for the approximate s...