Pareto-Dominance Based MOGP for Evolving Soccer Agents

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@InProceedings{Lazarus:2015:ieeeSSCI,

• author = "Christopher Lazarus",
• booktitle = "IEEE Symposium Series on Computational Intelligence",
• title = "Pareto-Dominance Based MOGP for Evolving Soccer Agents",
• year = "2015",
• pages = "280--287",
• abstract = "Robot behaviour generation is an attractive option to automatically produce robot controllers. Most high-level robot behaviours comprise multiple objectives that may be conflicting with each other. This research describes experiments using two Pareto-dominance based algorithms together with a Multiobjective Genetic Programming (MOGP) framework to evolve high-level robot behaviours using only primitive commands. The performance of hand-coded controllers are compared against controllers evolved using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Strength Pareto Evolutionary Algorithm 2 (SPEA2) algorithms. An additional comparison is also performed against controllers evolved using the weighted sum fitness function. The experiment results show that the Pareto dominance based MOGP performed better than the hand-coded and the weighted sum evolved controllers.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/SSCI.2015.49",
• month = dec,
• notes = "Also known as \cite{7376622}",

}

Genetic Programming entries for Christopher Lazarus

Citations