Analysis of a Batch Strategy for a Master-Worker Adaptive Selection Algorithm Framework

Christopher Jankee, Sébastien Verel, Bilel Derbel, Cyril Fonlupt

Abstract

We look into the design of a parallel adaptive algorithm embedded in a master-slave scheme. The adaptive algorithm under study selects online and in parallel for each slave-node one algorithm from a portfolio. Indeed, many open questions still arise when designing an online distributed strategy that attributes optimally algorithms to distribute resources. We suggest to analyze the relevance of existing sequential adaptive strategies related to multi-armed bandits to the master-slave distributed framework. In particular, the comprehensive experimental study focuses on the gain of computing power, the adaptive ability of selection strategies, and the communication cost of the parallel system. In fact, we propose an adaptive batch mode in which a sequence of algorithms is submitted to each slave computing node to face a possibly high communication cost.

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Paper Citation


in Harvard Style

Jankee C., Verel S., Derbel B. and Fonlupt C. (2017). Analysis of a Batch Strategy for a Master-Worker Adaptive Selection Algorithm Framework.In Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI, ISBN 978-989-758-274-5, pages 313-320. DOI: 10.5220/0006504203130320


in Bibtex Style

@conference{ijcci17,
author={Christopher Jankee and Sébastien Verel and Bilel Derbel and Cyril Fonlupt},
title={Analysis of a Batch Strategy for a Master-Worker Adaptive Selection Algorithm Framework},
booktitle={Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,},
year={2017},
pages={313-320},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006504203130320},
isbn={978-989-758-274-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,
TI - Analysis of a Batch Strategy for a Master-Worker Adaptive Selection Algorithm Framework
SN - 978-989-758-274-5
AU - Jankee C.
AU - Verel S.
AU - Derbel B.
AU - Fonlupt C.
PY - 2017
SP - 313
EP - 320
DO - 10.5220/0006504203130320