Parallel Patterns for Agent-based Evolutionary Computing

Jan Stypka; Piotr Anielski; Szymon Mentel; Daniel Krzywicki; Wojciech Turek; Aleksander Byrski; Marek Kisiel-Dorohinicki

doi:10.7494/csci.2016.17.1.83

Authors

Jan Stypka AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krakow
Piotr Anielski AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krakow
Szymon Mentel AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krakow
Daniel Krzywicki AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krakow
Wojciech Turek AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krakow
Aleksander Byrski AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krakow
Marek Kisiel-Dorohinicki AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krakow

DOI:

https://doi.org/10.7494/csci.2016.17.1.83

Keywords:

agent-based computing, functional programming, parallel pattern

Abstract

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.

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