Evolution of heterogeneous perceptual limits and indifference in competitive foraging
The collective behaviour of animal and human groups emerges from the individual decisions and actions of their constituent members. Recent research has revealed many ways in which the behaviour of groups can be influenced by differences amongst their constituent individuals. The existence of individ...
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description | The collective behaviour of animal and human groups emerges from the individual decisions and actions of their constituent members. Recent research has revealed many ways in which the behaviour of groups can be influenced by differences amongst their constituent individuals. The existence of individual differences that have implications for collective behaviour raises important questions. How are these differences generated and maintained? Are individual differences driven by exogenous factors, or are they a response to the social dilemmas these groups face? Here I consider the classic case of patch selection by foraging agents under conditions of social competition. I introduce a multilevel model wherein the perceptual sensitivities of agents evolve in response to their foraging success or failure over repeated patch selections. This model reveals a bifurcation in the population, creating a class of agents with no perceptual sensitivity. These agents exploit the social environment to avoid the costs of accurate perception, relying on other agents to make fitness rewards insensitive to the choice of foraging patch. This provides a individual-based evolutionary basis for models incorporating perceptual limits that have been proposed to explain observed deviations from the Ideal Free Distribution (IFD) in empirical studies, while showing that the common assumption in such models that agents share identical sensory limits is likely false. Further analysis of the model shows how agents develop perceptual strategic niches in response to environmental variability. The emergence of agents insensitive to reward differences also has implications for societal resource allocation problems, including the use of financial and prediction markets as mechanisms for aggregating collective wisdom. |
doi_str_mv | 10.1371/journal.pcbi.1008734 |
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These agents exploit the social environment to avoid the costs of accurate perception, relying on other agents to make fitness rewards insensitive to the choice of foraging patch. This provides a individual-based evolutionary basis for models incorporating perceptual limits that have been proposed to explain observed deviations from the Ideal Free Distribution (IFD) in empirical studies, while showing that the common assumption in such models that agents share identical sensory limits is likely false. Further analysis of the model shows how agents develop perceptual strategic niches in response to environmental variability. The emergence of agents insensitive to reward differences also has implications for societal resource allocation problems, including the use of financial and prediction markets as mechanisms for aggregating collective wisdom.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1008734</identifier><identifier>PMID: 33621223</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Animals ; Behavior, Animal ; Biological Evolution ; Biology and Life Sciences ; Competition ; Competitive Behavior ; Computer and Information Sciences ; Computer Simulation ; Decision making ; Ecosystem ; Environment ; Equilibrium ; Evolution ; Feeding Behavior - physiology ; Fitness ; Games ; Grasslands ; Humans ; Mathematical analysis ; Models, Theoretical ; Natural selection ; Navigation behavior ; Perception ; Physical Sciences ; Population ; Reproductive fitness ; Research and Analysis Methods ; Sensitivity and Specificity ; Social Behavior ; Social Sciences</subject><ispartof>PLoS computational biology, 2021-02, Vol.17 (2), p.e1008734-e1008734</ispartof><rights>2021 Richard P. Mann. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Richard P. Mann 2021 Richard P. 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Recent research has revealed many ways in which the behaviour of groups can be influenced by differences amongst their constituent individuals. The existence of individual differences that have implications for collective behaviour raises important questions. How are these differences generated and maintained? Are individual differences driven by exogenous factors, or are they a response to the social dilemmas these groups face? Here I consider the classic case of patch selection by foraging agents under conditions of social competition. I introduce a multilevel model wherein the perceptual sensitivities of agents evolve in response to their foraging success or failure over repeated patch selections. This model reveals a bifurcation in the population, creating a class of agents with no perceptual sensitivity. These agents exploit the social environment to avoid the costs of accurate perception, relying on other agents to make fitness rewards insensitive to the choice of foraging patch. This provides a individual-based evolutionary basis for models incorporating perceptual limits that have been proposed to explain observed deviations from the Ideal Free Distribution (IFD) in empirical studies, while showing that the common assumption in such models that agents share identical sensory limits is likely false. Further analysis of the model shows how agents develop perceptual strategic niches in response to environmental variability. The emergence of agents insensitive to reward differences also has implications for societal resource allocation problems, including the use of financial and prediction markets as mechanisms for aggregating collective wisdom.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Behavior, Animal</subject><subject>Biological Evolution</subject><subject>Biology and Life Sciences</subject><subject>Competition</subject><subject>Competitive Behavior</subject><subject>Computer and Information Sciences</subject><subject>Computer Simulation</subject><subject>Decision making</subject><subject>Ecosystem</subject><subject>Environment</subject><subject>Equilibrium</subject><subject>Evolution</subject><subject>Feeding Behavior - physiology</subject><subject>Fitness</subject><subject>Games</subject><subject>Grasslands</subject><subject>Humans</subject><subject>Mathematical analysis</subject><subject>Models, Theoretical</subject><subject>Natural selection</subject><subject>Navigation behavior</subject><subject>Perception</subject><subject>Physical Sciences</subject><subject>Population</subject><subject>Reproductive fitness</subject><subject>Research and Analysis Methods</subject><subject>Sensitivity and Specificity</subject><subject>Social Behavior</subject><subject>Social Sciences</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNptUk1r3DAQNaElSdP-g9IaeullN_qwLOtSKCFtA4FekrOQpZGjRbZcSV7Iv6-SdUJSepoZzXtPM8Orqo8YbTHl-HwXljgpv51177YYoY7T5qg6xYzRDaese_MiP6nepbRDqKSiPa5OKG0JJoSeVreX--CX7MJUB1vfQYYYBpggLKmeIWqY86J87d3ocqrVZGo3GWctRJg0lKLWYZwhu-z2UNsQ1eCm4X311iqf4MMaz6rbH5c3F782179_Xl18v95oRtq86QhtrSUMCDaWYmoaoVvLmG01EbjRnGNBkBIGc95xRZEWmHHWaYZwYyyiZ9Xng-7sQ5LrRZIkpd91iHJREFcHhAlqJ-foRhXvZVBOPj6EOEgVs9MepDG9Ior3iCrTmLYRlgEjlJd5NNemL1rf1t-WfgSjYcpR-VeirzuTu5ND2EsuEOa0LQJfV4EY_iyQshxd0uC9ejy4JI2gCDWckwL98g_0_9s1B5SOIaUI9nkYjOSDS55Y8sElcnVJoX16ucgz6ckW9C_MY7vU</recordid><startdate>20210201</startdate><enddate>20210201</enddate><creator>Mann, Richard P</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7QP</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-0701-1274</orcidid></search><sort><creationdate>20210201</creationdate><title>Evolution of heterogeneous perceptual limits and indifference in competitive foraging</title><author>Mann, Richard P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c526t-8236ff25e21df313d49c6f55f6c2914c771920a9d17787a30c915758c5014df03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Behavior, Animal</topic><topic>Biological Evolution</topic><topic>Biology and Life Sciences</topic><topic>Competition</topic><topic>Competitive Behavior</topic><topic>Computer and Information Sciences</topic><topic>Computer Simulation</topic><topic>Decision making</topic><topic>Ecosystem</topic><topic>Environment</topic><topic>Equilibrium</topic><topic>Evolution</topic><topic>Feeding Behavior - physiology</topic><topic>Fitness</topic><topic>Games</topic><topic>Grasslands</topic><topic>Humans</topic><topic>Mathematical analysis</topic><topic>Models, Theoretical</topic><topic>Natural selection</topic><topic>Navigation behavior</topic><topic>Perception</topic><topic>Physical Sciences</topic><topic>Population</topic><topic>Reproductive fitness</topic><topic>Research and Analysis Methods</topic><topic>Sensitivity and Specificity</topic><topic>Social Behavior</topic><topic>Social Sciences</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mann, Richard P</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</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>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mann, Richard P</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evolution of heterogeneous perceptual limits and indifference in competitive foraging</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2021-02-01</date><risdate>2021</risdate><volume>17</volume><issue>2</issue><spage>e1008734</spage><epage>e1008734</epage><pages>e1008734-e1008734</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>The collective behaviour of animal and human groups emerges from the individual decisions and actions of their constituent members. Recent research has revealed many ways in which the behaviour of groups can be influenced by differences amongst their constituent individuals. The existence of individual differences that have implications for collective behaviour raises important questions. How are these differences generated and maintained? Are individual differences driven by exogenous factors, or are they a response to the social dilemmas these groups face? Here I consider the classic case of patch selection by foraging agents under conditions of social competition. I introduce a multilevel model wherein the perceptual sensitivities of agents evolve in response to their foraging success or failure over repeated patch selections. This model reveals a bifurcation in the population, creating a class of agents with no perceptual sensitivity. These agents exploit the social environment to avoid the costs of accurate perception, relying on other agents to make fitness rewards insensitive to the choice of foraging patch. This provides a individual-based evolutionary basis for models incorporating perceptual limits that have been proposed to explain observed deviations from the Ideal Free Distribution (IFD) in empirical studies, while showing that the common assumption in such models that agents share identical sensory limits is likely false. Further analysis of the model shows how agents develop perceptual strategic niches in response to environmental variability. The emergence of agents insensitive to reward differences also has implications for societal resource allocation problems, including the use of financial and prediction markets as mechanisms for aggregating collective wisdom.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>33621223</pmid><doi>10.1371/journal.pcbi.1008734</doi><orcidid>https://orcid.org/0000-0003-0701-1274</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Animals Behavior, Animal Biological Evolution Biology and Life Sciences Competition Competitive Behavior Computer and Information Sciences Computer Simulation Decision making Ecosystem Environment Equilibrium Evolution Feeding Behavior - physiology Fitness Games Grasslands Humans Mathematical analysis Models, Theoretical Natural selection Navigation behavior Perception Physical Sciences Population Reproductive fitness Research and Analysis Methods Sensitivity and Specificity Social Behavior Social Sciences |
title | Evolution of heterogeneous perceptual limits and indifference in competitive foraging |
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