Computing applications such as metaheuristics-based optimization can greatly benefit from multi-core architectures available on modern supercomputers. In this paper, we describe an easy and efficient way to implement certain population-based algorithms (in the discussed case, multi-agent computing system) on such runtime environments. Our solution is based on an Erlang software library which implements dedicated parallel patterns. We provide technological details on our approach and discuss experimental results
Mathematica has proven itself to be a suitable platform on which to develop prototype Genetic Progr...
AbstractMetaheuristics resulting from the hybridization of multi-agent systems with evolutionary com...
The original publication is available at www.springerlink.comInternational audienceParaDisEO is a fr...
Computing applications such as metaheuristics-based optimization can greatly benefit from multi-core...
Computing applications such as metaheuristics-based optimization can greatly benefit from multi-core...
This paper considers how to use program shaping and algorithmic skeletons to parallelise a multi-age...
This paper considers how to use program shaping and algorithmic skeletons to parallelise a multi-age...
Evolutionary multi-agent systems (EMAS) play a critical role in many artificial intelligence applica...
Evolutionary multi-agent systems (EMAS) play a critical role in many artificial intelligence applica...
<p>Evolutionary multi-agent systems (EMAS) play a critical role in many artificial intelligence appl...
Abstract — Evolutionary algorithms (EAs) are a range of problem-solving techniques based on mechanis...
Supplementary data associated with this article can be found, in the online version, at http://dx.do...
An architecture of a distributed parallel genetic algorithm was developed to improve computing resou...
This thesis describes my PHD work carried out within the computer science and operations research gr...
The discovery process of data mining concerns an automatic extraction of interesting patterns and co...
Mathematica has proven itself to be a suitable platform on which to develop prototype Genetic Progr...
AbstractMetaheuristics resulting from the hybridization of multi-agent systems with evolutionary com...
The original publication is available at www.springerlink.comInternational audienceParaDisEO is a fr...
Computing applications such as metaheuristics-based optimization can greatly benefit from multi-core...
Computing applications such as metaheuristics-based optimization can greatly benefit from multi-core...
This paper considers how to use program shaping and algorithmic skeletons to parallelise a multi-age...
This paper considers how to use program shaping and algorithmic skeletons to parallelise a multi-age...
Evolutionary multi-agent systems (EMAS) play a critical role in many artificial intelligence applica...
Evolutionary multi-agent systems (EMAS) play a critical role in many artificial intelligence applica...
<p>Evolutionary multi-agent systems (EMAS) play a critical role in many artificial intelligence appl...
Abstract — Evolutionary algorithms (EAs) are a range of problem-solving techniques based on mechanis...
Supplementary data associated with this article can be found, in the online version, at http://dx.do...
An architecture of a distributed parallel genetic algorithm was developed to improve computing resou...
This thesis describes my PHD work carried out within the computer science and operations research gr...
The discovery process of data mining concerns an automatic extraction of interesting patterns and co...
Mathematica has proven itself to be a suitable platform on which to develop prototype Genetic Progr...
AbstractMetaheuristics resulting from the hybridization of multi-agent systems with evolutionary com...
The original publication is available at www.springerlink.comInternational audienceParaDisEO is a fr...