Collective homeostasis and time-resolved models of self-organised task allocation

Bernd Meyer, Anja Weidenmuller, Rui Chen, Julian Garcia

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    Abstract

    One of the main factors behind the amazing ecological success of social insects is their ability to flexibly allocate the colony s workforce to all the different tasks it has to address. Insights into the self-organised task allocation methods used for this have given rise to the design of an important class of bio-inspired algorithms for network control, industrial optimisation, and other applications. The most widely used class of models for self-organised task allocation, which also forms the core of these algorithms, are the so-called response threshold models. We revisit response threshold models with new experiments using temperature regulation in bumblebee colonies as the model system. We show that standard response threshold models do not fit our experiments and present a new, alternative behavioural model. This captures a fine-grained, time resolved picture of task engagement, which enables us to investigate task allocation with a different set of statistical methods (survival analysis). Using these we show that our model fits the experiment well and explains its salient aspects. We compare the effectiveness of the behaviour that our model describes with that of response threshold models and demonstrate that it can lead to more e cient task management when demands fluctuate. Our results have the potential to provide a basis for the design of new, more effcient task allocation algorithms for dynamic environments and to elucidate important biological questions, such as the functional role of inter-individual variation.
    Original languageEnglish
    Title of host publication9th EAI International Conference on Bioinspired Information and Communications Technologies (BICT 2015)
    EditorsJunichi Suzuki, Tadashi Nakano, Henry Hess
    Place of PublicationNew York NY USA
    PublisherAssociation for Computing Machinery (ACM)
    Pages1-10
    Number of pages10
    ISBN (Print)9781631901003
    DOIs
    Publication statusPublished - 2016
    EventEAI International Conference on Bioinspired Information and Communications Technologies (BICT 2015) - New York City, United States
    Duration: 3 Dec 20155 Dec 2015
    Conference number: 9th
    http://bionetics.org/2015/show/home

    Conference

    ConferenceEAI International Conference on Bioinspired Information and Communications Technologies (BICT 2015)
    Abbreviated titleBICT 2015
    CountryUnited States
    CityNew York City
    Period3/12/155/12/15
    Other9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)
    Internet address

    Cite this

    Meyer, B., Weidenmuller, A., Chen, R., & Garcia , J. (2016). Collective homeostasis and time-resolved models of self-organised task allocation. In J. Suzuki, T. Nakano, & H. Hess (Eds.), 9th EAI International Conference on Bioinspired Information and Communications Technologies (BICT 2015) (pp. 1-10). New York NY USA: Association for Computing Machinery (ACM). https://doi.org/10.4108/eai.3-12-2015.2262459
    Meyer, Bernd ; Weidenmuller, Anja ; Chen, Rui ; Garcia , Julian . / Collective homeostasis and time-resolved models of self-organised task allocation. 9th EAI International Conference on Bioinspired Information and Communications Technologies (BICT 2015). editor / Junichi Suzuki ; Tadashi Nakano ; Henry Hess. New York NY USA : Association for Computing Machinery (ACM), 2016. pp. 1-10
    @inproceedings{4e980cac18db4dd0b41c68a397a142f3,
    title = "Collective homeostasis and time-resolved models of self-organised task allocation",
    abstract = "One of the main factors behind the amazing ecological success of social insects is their ability to flexibly allocate the colony s workforce to all the different tasks it has to address. Insights into the self-organised task allocation methods used for this have given rise to the design of an important class of bio-inspired algorithms for network control, industrial optimisation, and other applications. The most widely used class of models for self-organised task allocation, which also forms the core of these algorithms, are the so-called response threshold models. We revisit response threshold models with new experiments using temperature regulation in bumblebee colonies as the model system. We show that standard response threshold models do not fit our experiments and present a new, alternative behavioural model. This captures a fine-grained, time resolved picture of task engagement, which enables us to investigate task allocation with a different set of statistical methods (survival analysis). Using these we show that our model fits the experiment well and explains its salient aspects. We compare the effectiveness of the behaviour that our model describes with that of response threshold models and demonstrate that it can lead to more e cient task management when demands fluctuate. Our results have the potential to provide a basis for the design of new, more effcient task allocation algorithms for dynamic environments and to elucidate important biological questions, such as the functional role of inter-individual variation.",
    author = "Bernd Meyer and Anja Weidenmuller and Rui Chen and Julian Garcia",
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    Meyer, B, Weidenmuller, A, Chen, R & Garcia , J 2016, Collective homeostasis and time-resolved models of self-organised task allocation. in J Suzuki, T Nakano & H Hess (eds), 9th EAI International Conference on Bioinspired Information and Communications Technologies (BICT 2015). Association for Computing Machinery (ACM), New York NY USA, pp. 1-10, EAI International Conference on Bioinspired Information and Communications Technologies (BICT 2015), New York City, United States, 3/12/15. https://doi.org/10.4108/eai.3-12-2015.2262459

    Collective homeostasis and time-resolved models of self-organised task allocation. / Meyer, Bernd; Weidenmuller, Anja; Chen, Rui; Garcia , Julian .

    9th EAI International Conference on Bioinspired Information and Communications Technologies (BICT 2015). ed. / Junichi Suzuki; Tadashi Nakano; Henry Hess. New York NY USA : Association for Computing Machinery (ACM), 2016. p. 1-10.

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    TY - GEN

    T1 - Collective homeostasis and time-resolved models of self-organised task allocation

    AU - Meyer, Bernd

    AU - Weidenmuller, Anja

    AU - Chen, Rui

    AU - Garcia , Julian

    PY - 2016

    Y1 - 2016

    N2 - One of the main factors behind the amazing ecological success of social insects is their ability to flexibly allocate the colony s workforce to all the different tasks it has to address. Insights into the self-organised task allocation methods used for this have given rise to the design of an important class of bio-inspired algorithms for network control, industrial optimisation, and other applications. The most widely used class of models for self-organised task allocation, which also forms the core of these algorithms, are the so-called response threshold models. We revisit response threshold models with new experiments using temperature regulation in bumblebee colonies as the model system. We show that standard response threshold models do not fit our experiments and present a new, alternative behavioural model. This captures a fine-grained, time resolved picture of task engagement, which enables us to investigate task allocation with a different set of statistical methods (survival analysis). Using these we show that our model fits the experiment well and explains its salient aspects. We compare the effectiveness of the behaviour that our model describes with that of response threshold models and demonstrate that it can lead to more e cient task management when demands fluctuate. Our results have the potential to provide a basis for the design of new, more effcient task allocation algorithms for dynamic environments and to elucidate important biological questions, such as the functional role of inter-individual variation.

    AB - One of the main factors behind the amazing ecological success of social insects is their ability to flexibly allocate the colony s workforce to all the different tasks it has to address. Insights into the self-organised task allocation methods used for this have given rise to the design of an important class of bio-inspired algorithms for network control, industrial optimisation, and other applications. The most widely used class of models for self-organised task allocation, which also forms the core of these algorithms, are the so-called response threshold models. We revisit response threshold models with new experiments using temperature regulation in bumblebee colonies as the model system. We show that standard response threshold models do not fit our experiments and present a new, alternative behavioural model. This captures a fine-grained, time resolved picture of task engagement, which enables us to investigate task allocation with a different set of statistical methods (survival analysis). Using these we show that our model fits the experiment well and explains its salient aspects. We compare the effectiveness of the behaviour that our model describes with that of response threshold models and demonstrate that it can lead to more e cient task management when demands fluctuate. Our results have the potential to provide a basis for the design of new, more effcient task allocation algorithms for dynamic environments and to elucidate important biological questions, such as the functional role of inter-individual variation.

    UR - http://eudl.eu/doi/10.4108/eai.3-12-2015.2262459

    U2 - 10.4108/eai.3-12-2015.2262459

    DO - 10.4108/eai.3-12-2015.2262459

    M3 - Conference Paper

    SN - 9781631901003

    SP - 1

    EP - 10

    BT - 9th EAI International Conference on Bioinspired Information and Communications Technologies (BICT 2015)

    A2 - Suzuki, Junichi

    A2 - Nakano, Tadashi

    A2 - Hess, Henry

    PB - Association for Computing Machinery (ACM)

    CY - New York NY USA

    ER -

    Meyer B, Weidenmuller A, Chen R, Garcia J. Collective homeostasis and time-resolved models of self-organised task allocation. In Suzuki J, Nakano T, Hess H, editors, 9th EAI International Conference on Bioinspired Information and Communications Technologies (BICT 2015). New York NY USA: Association for Computing Machinery (ACM). 2016. p. 1-10 https://doi.org/10.4108/eai.3-12-2015.2262459