#NOME?
Data
2017
Autores
Dal Piccol Sotto, Leo Francoso 
de Melo, Vinicius Veloso
Basgalupp, Marcio Porto
Tipo
Artigo
Título da Revista
ISSN da Revista
Título de Volume
Resumo
The Ant Trail problem has been widely investigated as a benchmark for automatic design of algorithms. One must design the program of a virtual ant to collect all pieces of food located in different places of a map, which may have obstacles, in a predefined limit of steps. This is a challenging problem, but several evolutionary computation (EC) researchers have reported methods with good results. In this paper, we propose an EC method called -linear genetic programming (-LGP), a variation of the well-known linear genetic programming (LGP) algorithm. Starting with an LGP based only on effective macro- and micro-mutations, the -LGP proposed in this work consists in extending how the individuals are chosen for reproduction. In this model, a number () of mutations is applied to each individual, trying to explore its neighboring fitness regions
such individual might be replaced by one of its children according to different criteria. Several configurations were tested over three different trails: the Santa Fe, the Los Altos Hill, and the John Muir. Results show a very significant improvement over LGP by using this proposed variation. Also, -LGP outperformed not only LGP, but also other state-of-the-art methods from the literature.
such individual might be replaced by one of its children according to different criteria. Several configurations were tested over three different trails: the Santa Fe, the Los Altos Hill, and the John Muir. Results show a very significant improvement over LGP by using this proposed variation. Also, -LGP outperformed not only LGP, but also other state-of-the-art methods from the literature.
Descrição
Citação
Knowledge And Information Systems. London, v. 52, n. 2, p. 445-465, 2017.