Abstract- Choosing the best parameter setting is a wellknown important and challenging task in Evolutionary Algorithms (EAs). As one of the earliest parameter tuning techniques, th...
In order to overcome the low convergence speed and prematurity of classical genetic algorithm, an improved method named directional self-learning of genetic algorithm (DSLGA) is p...
This paper explores some simple evolutionary strategies for an elitist, steady-state Pareto-based multi-objective evolutionary algorithm. The experimental framework is based on the...
Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive cont...
Monte-Carlo tree search is a powerful paradigm for the game of Go. We present a parallel Master-Slave algorithm for Monte-Carlo tree search. We experimented the algorithm on a netw...