Derivation of a micro-macro link for collective decision-making systems uncover network features based on drift measurements

Heiko Hamann; Gabriele Valentini; Yara Khaluf; Marco Dorigo

doi:10.1007/978-3-319-10762-2_18

Derivation of a micro-macro link for collective decision-making systems uncover network features based on drift measurements

Heiko Hamann, Gabriele Valentini, Yara Khaluf, Marco Dorigo

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Academic › peer-review

23 Citations (Scopus)

Abstract

Relating microscopic features (individual level) to macroscopic features (swarm level) of self-organizing collective systems is challenging. In this paper, we report the mathematical derivation of a macroscopic model starting from a microscopic one for the example of collective decision-making. The collective system is based on the application of a majority rule over groups of variable size which is modeled by chemical reactions (micro-model). From an approximated master equation we derive the drift term of a stochastic differential equation (macromodel) which is applied to predict the expected swarm behavior. We give a recursive definition of the polynomials defining this drift term. Our results are validated by Gillespie simulations and simulations of the locust alignment.

Original language	English
Title of host publication	Parallel Problem Solving from Nature -- PPSN XIII
Subtitle of host publication	13th International Conference, Ljubljana, Slovenia, September 13-17, 2014, Proceedings
Editors	T. Bartz-Beielstein, J. Branke, B. Filipic, J. Smith
Place of Publication	Cham
Publisher	Springer
Pages	181-190
Number of pages	10
Volume	8672
ISBN (Electronic)	9783319107622
ISBN (Print)	9783319107615
DOIs	https://doi.org/10.1007/978-3-319-10762-2_18
Publication status	Published - Sep 2014
Externally published	Yes
Event	Parallel Problem Solving from Nature -- PPSN XIII : 13th International Conference - Ljubljana, Slovenia Duration: 13 Sep 2014 → 17 Sep 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer Verlag
ISSN (Print)	0302-9743

Conference

Conference	Parallel Problem Solving from Nature -- PPSN XIII
Country/Territory	Slovenia
City	Ljubljana
Period	13/09/14 → 17/09/22

Access to Document

10.1007/978-3-319-10762-2_18

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Hamann, H., Valentini, G., Khaluf, Y., & Dorigo, M. (2014). Derivation of a micro-macro link for collective decision-making systems uncover network features based on drift measurements. In T. Bartz-Beielstein, J. Branke, B. Filipic, & J. Smith (Eds.), Parallel Problem Solving from Nature -- PPSN XIII : 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014, Proceedings (Vol. 8672, pp. 181-190). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Springer. https://doi.org/10.1007/978-3-319-10762-2_18

Hamann, Heiko ; Valentini, Gabriele ; Khaluf, Yara et al. / Derivation of a micro-macro link for collective decision-making systems uncover network features based on drift measurements. Parallel Problem Solving from Nature -- PPSN XIII : 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014, Proceedings. editor / T. Bartz-Beielstein ; J. Branke ; B. Filipic ; J. Smith. Vol. 8672 Cham : Springer, 2014. pp. 181-190 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Relating microscopic features (individual level) to macroscopic features (swarm level) of self-organizing collective systems is challenging. In this paper, we report the mathematical derivation of a macroscopic model starting from a microscopic one for the example of collective decision-making. The collective system is based on the application of a majority rule over groups of variable size which is modeled by chemical reactions (micro-model). From an approximated master equation we derive the drift term of a stochastic differential equation (macromodel) which is applied to predict the expected swarm behavior. We give a recursive definition of the polynomials defining this drift term. Our results are validated by Gillespie simulations and simulations of the locust alignment.",

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Hamann, H, Valentini, G, Khaluf, Y & Dorigo, M 2014, Derivation of a micro-macro link for collective decision-making systems uncover network features based on drift measurements. in T Bartz-Beielstein, J Branke, B Filipic & J Smith (eds), Parallel Problem Solving from Nature -- PPSN XIII : 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014, Proceedings. vol. 8672, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, Cham, pp. 181-190, Parallel Problem Solving from Nature -- PPSN XIII , Ljubljana, Slovenia, 13/09/14. https://doi.org/10.1007/978-3-319-10762-2_18

Derivation of a micro-macro link for collective decision-making systems uncover network features based on drift measurements. / Hamann, Heiko; Valentini, Gabriele; Khaluf, Yara et al.

Parallel Problem Solving from Nature -- PPSN XIII : 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014, Proceedings. ed. / T. Bartz-Beielstein; J. Branke; B. Filipic; J. Smith. Vol. 8672 Cham : Springer, 2014. p. 181-190 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Academic › peer-review

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AU - Valentini, Gabriele

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N1 - Publisher Copyright: © Springer International Publishing Switzerland 2014.

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AB - Relating microscopic features (individual level) to macroscopic features (swarm level) of self-organizing collective systems is challenging. In this paper, we report the mathematical derivation of a macroscopic model starting from a microscopic one for the example of collective decision-making. The collective system is based on the application of a majority rule over groups of variable size which is modeled by chemical reactions (micro-model). From an approximated master equation we derive the drift term of a stochastic differential equation (macromodel) which is applied to predict the expected swarm behavior. We give a recursive definition of the polynomials defining this drift term. Our results are validated by Gillespie simulations and simulations of the locust alignment.

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Hamann H, Valentini G, Khaluf Y, Dorigo M. Derivation of a micro-macro link for collective decision-making systems uncover network features based on drift measurements. In Bartz-Beielstein T, Branke J, Filipic B, Smith J, editors, Parallel Problem Solving from Nature -- PPSN XIII : 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014, Proceedings. Vol. 8672. Cham: Springer. 2014. p. 181-190. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-10762-2_18

Derivation of a micro-macro link for collective decision-making systems uncover network features based on drift measurements

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