Parallel Patterns for Agent-based Evolutionary Computing

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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Published

2016-04-06

How to Cite

Stypka, J., Anielski, P., Mentel, S., Krzywicki, D., Turek, W., Byrski, A., & Kisiel-Dorohinicki, M. (2016). Parallel Patterns for Agent-based Evolutionary Computing. Computer Science, 17(1), 83. https://doi.org/10.7494/csci.2016.17.1.83

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