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This paper addresses the cooperative transport of a heavy object, called prey, towards a sporadically changing target location by a group of robots. The study is focused on the sit...
We show how the understandability and speed of genetic programming classification algorithms can be improved, without affecting the classification accuracy. By analyzing the dec...
We consider the problem of finding small Golomb rulers, a hard combinatorial optimization task. This problem is here tackled by means of a hybrid evolutionary algorithm (EA). This...
Mathematical modeling of the spread of infectious diseases is a well established field with high practical importance. Underlying most analytical approaches is the assumption of �...
In this paper we present AntHocNet, a new algorithm for routing in mobile ad hoc networks. Due to the ever changing topology and limited bandwidth it is very hard to establish and ...
Gianni Di Caro, Frederick Ducatelle, Luca Maria Ga...
Considerable research effort has been spent in trying to formulate a good definition of GA-Hardness. Given an instance of a problem, the objective is to estimate the performance of...
Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person’s...
The investigation of evolutionary algorithms as adaptation schemes has a long history starting with Holland (1975). The Ising model from physics leads to a variety of different pr...
Patrick Briest, Dimo Brockhoff, Bastian Degener, M...
Abstract. Evolution Strategies, Evolutionary Algorithms based on Gaussian mutation and deterministic selection, are today considered the best choice as far as parameter optimizatio...
It is typical for the EA community that theory follows experiments. Most theoretical approaches use some model of the considered evolutionary algorithm (EA) but there is also some ...
Patrick Briest, Dimo Brockhoff, Bastian Degener, M...