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      A Simple Threshold Rule Is Sufficient to Explain Sophisticated Collective Decision-Making

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          Abstract

          Decision-making animals can use slow-but-accurate strategies, such as making multiple comparisons, or opt for simpler, faster strategies to find a ‘good enough’ option. Social animals make collective decisions about many group behaviours including foraging and migration. The key to the collective choice lies with individual behaviour. We present a case study of a collective decision-making process (house-hunting ants, Temnothorax albipennis), in which a previously proposed decision strategy involved both quality-dependent hesitancy and direct comparisons of nests by scouts. An alternative possible decision strategy is that scouting ants use a very simple quality-dependent threshold rule to decide whether to recruit nest-mates to a new site or search for alternatives. We use analytical and simulation modelling to demonstrate that this simple rule is sufficient to explain empirical patterns from three studies of collective decision-making in ants, and can account parsimoniously for apparent comparison by individuals and apparent hesitancy (recruitment latency) effects, when available nests differ strongly in quality. This highlights the need to carefully design experiments to detect individual comparison. We present empirical data strongly suggesting that best-of-n comparison is not used by individual ants, although individual sequential comparisons are not ruled out. However, by using a simple threshold rule, decision-making groups are able to effectively compare options, without relying on any form of direct comparison of alternatives by individuals. This parsimonious mechanism could promote collective rationality in group decision-making.

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          Consensus decision making in animals.

          Individual animals routinely face decisions that are crucial to their fitness. In social species, however, many of these decisions need to be made jointly with other group members because the group will split apart unless a consensus is reached. Here, we review empirical and theoretical studies of consensus decision making, and place them in a coherent framework. In particular, we classify consensus decisions according to the degree to which they involve conflict of interest between group members, and whether they involve either local or global communication; we ask, for different categories of consensus decision, who makes the decision, what are the underlying mechanisms, and what are the functional consequences. We conclude that consensus decision making is common in non-human animals, and that cooperation between group members in the decision-making process is likely to be the norm, even when the decision involves significant conflict of interest.
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            Models of division of labor in social insects.

            Division of labor is one of the most basic and widely studied aspects of colony behavior in social insects. Studies of division of labor are concerned with the integration of individual worker behavior into colony level task organization and with the question of how regulation of division of labor may contribute to colony efficiency. Here we describe and critique the current models concerned with the proximate causes of division of labor in social insects. The models have identified various proximate mechanisms to explain division of labor, based on both internal and external factors. On the basis of these factors, we suggest a classification of the models. We first describe the different types of models and then review the empirical evidence supporting them. The models to date may be considered preliminary and exploratory; they have advanced our understanding by suggesting possible mechanisms for division of labor and by revealing how individual and colony-level behavior may be related. They suggest specific hypotheses that can be tested by experiment and so may lead to the development of more powerful and integrative explanatory models.
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              Consumer Preference for a No‐Choice Option

              Ravi Dhar (1997)
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                24 May 2011
                : 6
                : 5
                : e19981
                Affiliations
                [1 ]School of Biological Sciences, University of Bristol, Bristol, United Kingdom
                [2 ]York Centre for Complex Systems Analysis, Department of Biology, University of York, York, United Kingdom
                [3 ]Department of Computer Science and Kroto Research Institute, University of Sheffield, Sheffield, United Kingdom
                University of Utah, United States of America
                Author notes

                Conceived and designed the experiments: EJHR NRF. Performed the experiments: EJHR SE SO. Analyzed the data: EJHR. Wrote the paper: EJHR NRF JARM. Conceived and designed the model: EJHR JARM. Performed analytical modelling: JARM. Performed simulation modelling: EJHR JARM.

                Article
                PONE-D-10-06337
                10.1371/journal.pone.0019981
                3101226
                21629645
                0c8dd353-e572-42d5-bea2-81b87372ad9d
                Robinson et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 6 December 2010
                : 22 April 2011
                Page count
                Pages: 11
                Categories
                Research Article
                Biology
                Ecology
                Behavioral Ecology
                Theoretical Ecology
                Evolutionary Biology
                Animal Behavior
                Behavioral Ecology
                Theoretical Biology
                Zoology
                Animal Behavior
                Entomology

                Uncategorized
                Uncategorized

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