DocumentCode :
3581220
Title :
Evolving directed graphs with artificial bee colony algorithm
Author :
Xianneng Li ; Guangfei Yang ; Hirasawa, Kotaro
Author_Institution :
Grad. Sch. of Inf., Waseda Univ., Kitakyushu, Japan
fYear :
2014
Firstpage :
89
Lastpage :
94
Abstract :
Artificial bee colony (ABC) algorithm is a relatively new optimization technique that simulates the intelligent foraging behavior of honey bee swarms. It has been applied to several optimization domains to show its efficient evolution ability. In this paper, ABC algorithm is applied for the first time to evolve a directed graph chromosome structure, which derived from a recent graph-based evolutionary algorithm called genetic network programming (GNP). Consequently, it is explored to new application domains which can be efficiently modeled by the directed graph of GNP. In this work, a problem of controlling the agents´s behavior under a wellknown benchmark testbed called Tileworld are solved using the ABC-based evolution strategy. Its performance is compared with several very well-known methods for evolving computer programs, including standard GNP with crossover/mutation, genetic programming (GP) and reinforcement learning (RL).
Keywords :
directed graphs; genetic algorithms; swarm intelligence; ABC algorithm; GNP; artificial bee colony algorithm; directed graph chromosome structure; genetic network programming; optimization technique; swarm intelligence; Algorithm design and analysis; Artificial neural networks; Computational modeling; Computers; Economic indicators; agent control; artificial bee colony; computer programs; directed graph; genetic network programming;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Applications (ISDA), 2014 14th International Conference on
Print_ISBN :
978-1-4799-7937-0
Type :
conf
DOI :
10.1109/ISDA.2014.7066282
Filename :
7066282
Link To Document :
بازگشت