— Genetic programming is the usage of the paradigm of survival of the fittest in scientific computing. It is applied to evolve solutions to problems where dependencies between ...
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incre...
The paper is concerned with the computational evaluation and comparison of a new family of conflict-based branching heuristics for evolved DPLL Satisfiability solvers. Such a fami...
In this paper we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to ...
Configurable software lets users customize applications in many ways, and is becoming increasingly prevalent. Regression testing is an important but expensive way to build confide...