Diverse Stochasticity Leads a Colony of Ants to Optimal Foraging
A mathematical model of garden ants (Laius japonicus) is introduced herein to investigate the relationship between the distribution of the degree of stochasticity in following pheromone trails and the group foraging efficiency. Numerical simulations of the model indicate that depending on the system...
Gespeichert in:
| Veröffentlicht in: | arXiv.org 2019-01 |
|---|---|
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | arXiv.org |
| container_volume | |
| creator | Shiraishi, Masashi Takeuchi, Rito Nakagawa, Hiroyuki Nishimura, Shin I Awazu, Akinori Nishimori, Hiraku |
| description | A mathematical model of garden ants (Laius japonicus) is introduced herein to investigate the relationship between the distribution of the degree of stochasticity in following pheromone trails and the group foraging efficiency. Numerical simulations of the model indicate that depending on the systematic change of the feeding environment, the optimal distribution of stochasticity shifts from a mixture of almost deterministic and mildly stochastic ants to a contrasted mixture of almost deterministic ants and highly stochastic ants. In addition, the interaction between the stochasticity and the pheromone path regulates the dynamics of the foraging efficiency optimization. Stochasticity could strengthen the collective efficiency when stochasticity to the sensitivity of pheromone for ants is introduced in the model. |
| format | Article |
| fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2073243579</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2073243579</sourcerecordid><originalsourceid>FETCH-proquest_journals_20732435793</originalsourceid><addsrcrecordid>eNqNyrEKwjAUQNEgCBbtPzxwLsSksbop1eIgOOheQk1rSs2reanQv9fBD3C6w7kTFgkpV8kmFWLGYqKWcy7WmVBKRmx3sG_jycA1YPXQFGxlwwhno-8EGnLs0I2ANexdIAgIlz7Yp-6gQK8b65oFm9a6IxP_OmfL4njLT0nv8TUYCmWLg3dfKgXPpEilyrbyv-sD_NE4hQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2073243579</pqid></control><display><type>article</type><title>Diverse Stochasticity Leads a Colony of Ants to Optimal Foraging</title><source>World Web Journals</source><creator>Shiraishi, Masashi ; Takeuchi, Rito ; Nakagawa, Hiroyuki ; Nishimura, Shin I ; Awazu, Akinori ; Nishimori, Hiraku</creator><creatorcontrib>Shiraishi, Masashi ; Takeuchi, Rito ; Nakagawa, Hiroyuki ; Nishimura, Shin I ; Awazu, Akinori ; Nishimori, Hiraku</creatorcontrib><description>A mathematical model of garden ants (Laius japonicus) is introduced herein to investigate the relationship between the distribution of the degree of stochasticity in following pheromone trails and the group foraging efficiency. Numerical simulations of the model indicate that depending on the systematic change of the feeding environment, the optimal distribution of stochasticity shifts from a mixture of almost deterministic and mildly stochastic ants to a contrasted mixture of almost deterministic ants and highly stochastic ants. In addition, the interaction between the stochasticity and the pheromone path regulates the dynamics of the foraging efficiency optimization. Stochasticity could strengthen the collective efficiency when stochasticity to the sensitivity of pheromone for ants is introduced in the model.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Animal behavior ; Ants ; Computer simulation ; Efficiency ; Mathematical models ; Pheromones</subject><ispartof>arXiv.org, 2019-01</ispartof><rights>2019. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,780</link.rule.ids></links><search><creatorcontrib>Shiraishi, Masashi</creatorcontrib><creatorcontrib>Takeuchi, Rito</creatorcontrib><creatorcontrib>Nakagawa, Hiroyuki</creatorcontrib><creatorcontrib>Nishimura, Shin I</creatorcontrib><creatorcontrib>Awazu, Akinori</creatorcontrib><creatorcontrib>Nishimori, Hiraku</creatorcontrib><title>Diverse Stochasticity Leads a Colony of Ants to Optimal Foraging</title><title>arXiv.org</title><description>A mathematical model of garden ants (Laius japonicus) is introduced herein to investigate the relationship between the distribution of the degree of stochasticity in following pheromone trails and the group foraging efficiency. Numerical simulations of the model indicate that depending on the systematic change of the feeding environment, the optimal distribution of stochasticity shifts from a mixture of almost deterministic and mildly stochastic ants to a contrasted mixture of almost deterministic ants and highly stochastic ants. In addition, the interaction between the stochasticity and the pheromone path regulates the dynamics of the foraging efficiency optimization. Stochasticity could strengthen the collective efficiency when stochasticity to the sensitivity of pheromone for ants is introduced in the model.</description><subject>Animal behavior</subject><subject>Ants</subject><subject>Computer simulation</subject><subject>Efficiency</subject><subject>Mathematical models</subject><subject>Pheromones</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNqNyrEKwjAUQNEgCBbtPzxwLsSksbop1eIgOOheQk1rSs2reanQv9fBD3C6w7kTFgkpV8kmFWLGYqKWcy7WmVBKRmx3sG_jycA1YPXQFGxlwwhno-8EGnLs0I2ANexdIAgIlz7Yp-6gQK8b65oFm9a6IxP_OmfL4njLT0nv8TUYCmWLg3dfKgXPpEilyrbyv-sD_NE4hQ</recordid><startdate>20190104</startdate><enddate>20190104</enddate><creator>Shiraishi, Masashi</creator><creator>Takeuchi, Rito</creator><creator>Nakagawa, Hiroyuki</creator><creator>Nishimura, Shin I</creator><creator>Awazu, Akinori</creator><creator>Nishimori, Hiraku</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20190104</creationdate><title>Diverse Stochasticity Leads a Colony of Ants to Optimal Foraging</title><author>Shiraishi, Masashi ; Takeuchi, Rito ; Nakagawa, Hiroyuki ; Nishimura, Shin I ; Awazu, Akinori ; Nishimori, Hiraku</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_20732435793</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Animal behavior</topic><topic>Ants</topic><topic>Computer simulation</topic><topic>Efficiency</topic><topic>Mathematical models</topic><topic>Pheromones</topic><toplevel>online_resources</toplevel><creatorcontrib>Shiraishi, Masashi</creatorcontrib><creatorcontrib>Takeuchi, Rito</creatorcontrib><creatorcontrib>Nakagawa, Hiroyuki</creatorcontrib><creatorcontrib>Nishimura, Shin I</creatorcontrib><creatorcontrib>Awazu, Akinori</creatorcontrib><creatorcontrib>Nishimori, Hiraku</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shiraishi, Masashi</au><au>Takeuchi, Rito</au><au>Nakagawa, Hiroyuki</au><au>Nishimura, Shin I</au><au>Awazu, Akinori</au><au>Nishimori, Hiraku</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Diverse Stochasticity Leads a Colony of Ants to Optimal Foraging</atitle><jtitle>arXiv.org</jtitle><date>2019-01-04</date><risdate>2019</risdate><eissn>2331-8422</eissn><abstract>A mathematical model of garden ants (Laius japonicus) is introduced herein to investigate the relationship between the distribution of the degree of stochasticity in following pheromone trails and the group foraging efficiency. Numerical simulations of the model indicate that depending on the systematic change of the feeding environment, the optimal distribution of stochasticity shifts from a mixture of almost deterministic and mildly stochastic ants to a contrasted mixture of almost deterministic ants and highly stochastic ants. In addition, the interaction between the stochasticity and the pheromone path regulates the dynamics of the foraging efficiency optimization. Stochasticity could strengthen the collective efficiency when stochasticity to the sensitivity of pheromone for ants is introduced in the model.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | EISSN: 2331-8422 |
| ispartof | arXiv.org, 2019-01 |
| issn | 2331-8422 |
| language | eng |
| recordid | cdi_proquest_journals_2073243579 |
| source | World Web Journals |
| subjects | Animal behavior Ants Computer simulation Efficiency Mathematical models Pheromones |
| title | Diverse Stochasticity Leads a Colony of Ants to Optimal Foraging |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-07T19%3A33%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Diverse%20Stochasticity%20Leads%20a%20Colony%20of%20Ants%20to%20Optimal%20Foraging&rft.jtitle=arXiv.org&rft.au=Shiraishi,%20Masashi&rft.date=2019-01-04&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2073243579%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2073243579&rft_id=info:pmid/&rfr_iscdi=true |