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Journal ArticleDOI

Modulation of trail laying in the ant Lasius niger (Hymenoptera: Formicidae) and its role in the collective selection of a food source

01 Nov 1993-Journal of Insect Behavior (Springer)-Vol. 6, Iss: 6, pp 751-759
TL;DR: Simulations of this model showed that the observed modulation of trail laying with respect to food source quality is sufficient in itself to account for the systematic selection of the richer source seen in the experiments.
Abstract: Foragers of the ant Lasius nigerexploiting a 1 Msugar source were found to lay 43 %more trail marks than those exploiting a 0.05 or a 0.1 Msource. The trail laying per forager decreased during the course of individual recruitment episodes, and the mean lifetime of the trail pheromone was estimated to be 47 min. A mathematical function describing the probability that a forager chooses one of two paths in relation to the amount of trail pheromone on them closely fitted experimental data. These results were incorporated into a model describing the recruitment dynamics of L. niger.Simulations of this model showed that the observed modulation of trail laying with respect to food source quality is sufficient in itself to account for the systematic selection of the richer source seen in the experiments.
Citations
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Book
01 Jan 1999
TL;DR: This chapter contains sections titled: Combinatorial Optimization, The ACO Metaheuristic, How Do I Apply ACO?
Abstract: This chapter contains sections titled: Combinatorial Optimization, The ACO Metaheuristic, How Do I Apply ACO?, Other Metaheuristics, Bibliographical Remarks, Things to Remember, Thought and Computer Exercises

1,756 citations

Journal ArticleDOI
TL;DR: It is argued that the key to understanding collective behaviour lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals.
Abstract: In recent years, the concept of self-organization has been used to understand collective behaviour of animals. The central tenet of self-organization is that simple repeated interactions between individuals can produce complex adaptive patterns at the level of the group. Inspiration comes from patterns seen in physical systems, such as spiralling chemical waves, which arise without complexity at the level of the individual units of which the system is composed. The suggestion is that biological structures such as termite mounds, ant trail networks and even human crowds can be explained in terms of repeated interactions between the animals and their environment, without invoking individual complexity. Here, I review cases in which the self-organization approach has been successful in explaining collective behaviour of animal groups and societies. Ant pheromone trail networks, aggregation of cockroaches, the applause of opera audiences and the migration of fish schools have all been accurately described in terms of individuals following simple sets of rules. Unlike the simple units composing physical systems, however, animals are themselves complex entities, and other examples of collective behaviour, such as honey bee foraging with its myriad of dance signals and behavioural cues, cannot be fully understood in terms of simple individuals alone. I argue that the key to understanding collective behaviour lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals. These principles, such as positive feedback, response thresholds and individual integrity, are repeatedly observed in very different animal societies. The future of collective behaviour research lies in classifying these principles, establishing the properties they produce at a group level and asking why they have evolved in so many different and distinct natural systems. Ultimately, this research could inform not only our understanding of animal societies, but also the principles by which we organize our own society.

892 citations


Cites background from "Modulation of trail laying in the a..."

  • ...Thus, when trail following ants make the choice between two bridges they detect a higher concentration of pheromone on one of the bridges, the shorter one (Beckers et al. 1993)....

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Book ChapterDOI
01 Jan 2003
TL;DR: The field of ACO algorithms is very lively, as testified, for example, by the successful biannual workshop (ANTS—From Ant Colonies to Artificial Ants: A Series of International Workshops on Ant Algorithms; http://iridia.ulb.ac.be/~ants/) where researchers meet to discuss the properties ofACO and other ant algorithms.
Abstract: The field of ACO algorithms is very lively, as testified, for example, by the successful biannual workshop (ANTS—From Ant Colonies to Artificial Ants: A Series of International Workshops on Ant Algorithms; http://iridia.ulb.ac.be/~ants/) where researchers meet to discuss the properties of ACO and other ant algorithms, both theoretically and experimentally.

890 citations


Cites background from "Modulation of trail laying in the a..."

  • ...complicate than those solved by real ants, we gave artificial ants some extra capacities, like a memory (used to implement constraints and t o allow the ants to retrace their path back to the nest without errors) and the ca pacity of depositing a quantity of pheromone proportional to the quality of the so luti n produced (a similar behavior is observed also in some real ants species i n which the quantity of pheromone deposited while returning to the nest from a food s urce is proportional to the quality of the food source found [3])....

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Journal ArticleDOI
TL;DR: A novel method of achieving load balancing in telecommunications networks using ant-based control, which is shown to result in fewer call failures than the other methods, while exhibiting many attractive features of distributed control.
Abstract: This article describes a novel method of achieving load balancing in telecommunications networks. A simulated network models a typical distribution of calls between nodes; nodes carrying an excess ...

838 citations

Book
27 Sep 2010
TL;DR: This paper aims to demonstrate the efforts towards in-situ applicability of EMMARM, as to provide real-time information about the physical and social contexts in which individuals and institutions operate.
Abstract: Acknowledgments ix Chapter 1: Introduction 1 Chapter 2: Coming Together 14 Chapter 3: Information Transfer 44 Chapter 4: Making Decisions 77 Chapter 5: Moving Together 101 Chapter 6: Synchronization 130 Chapter 7: Structures 151 Chapter 8: Regulation 173 Chapter 9: Complicated Interactions 198 Chapter 10: The Evolution of Co-operation 223 Chapter 11: Conclusions 253 References 259 Index 293

755 citations

References
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Journal ArticleDOI
TL;DR: A minimal model shows how the exploratory pattern may be generated by the individual workers' simple trail-laying and -following behavior, illustrating how complex collective structures in insect colonies may be based on self-organization.
Abstract: Workers of the Argentine ant, Iridomyrmex humilis,start to explore a chemically unmarked territory randomly. As the exploratory front advances, other explorers are recruited and a trail extends from it to the nest. Whereas recruitment trails are generally constructed between two points, these exploratory trails have no fixed destination, and strongly resemble the foraging patterns of army ants. A minimal model shows how the exploratory pattern may be generated by the individual workers' simple trail-laying and -following behavior, illustrating how complex collective structures in insect colonies may be based on self-organization.

957 citations


"Modulation of trail laying in the a..." refers methods in this paper

  • ...This function was used previously to quantify path choice in the ant Iridomyrmex humilis, and an experimental fitting gave n = 2 and k = 20 (Deneubourg et al., 1990)....

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Journal ArticleDOI
TL;DR: It is suggested that honey bee colonies possess decentralized decision-making because it combines effectiveness with simplicity of communication and computation within a colony.
Abstract: A honey bee colony can skillfully choose among nectar sources. It will selectively exploit the most profitable source in an array and will rapidly shift its foraging efforts following changes in the array. How does this colony-level ability emerge from the behavior of individual bees? The answer lies in understanding how bees modulate their colony's rates of recruitment and abandonment for nectar sources in accordance with the profitability of each source. A forager modulates its behavior in relation to nectar source profitability: as profitability increases, the tempo of foraging increases, the intensity of dancing increases, and the probability of abandoning the source decreases. How does a forager assess the profitability of its nectar source? Bees accomplish this without making comparisons among nectar sources. Neither do the foragers compare different nectar sources to determine the relative profitability of any one source, nor do the food storers compare different nectar loads and indicate the relative profitability of each load to the foragers. Instead, each forager knows only about its particular nectar source and independently calculates the absolute profitability of its source. Even though each of a colony's foragers operates with extremely limited information about the colony's food sources, together they will generate a coherent colonylevel response to different food sources in which better ones are heavily exploited and poorer ones are abandoned. This is shown by a computer simulation of nectar-source selection by a colony in which foragers behave as described above. Nectar-source selection by honey bee colonies is a process of natural selection among alternative nectar sources as foragers from more profitable sources “survive” (continue visiting their source) longer and “reproduce” (recruit other foragers) better than do foragers from less profitable sources. Hence this colonial decision-making is based on decentralized control. We suggest that honey bee colonies possess decentralized decision-making because it combines effectiveness with simplicity of communication and computation within a colony.

539 citations


"Modulation of trail laying in the a..." refers background in this paper

  • ...…context and in relation to the richness of the food source, the foragers modulate the strength of their waggle dancing, the tempo of their visits to the food source, their likelihood of returning there (Seeley et al., 1991; Camazine and Sneyd, 1991), and the receptivity of the workers in the nest....

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  • ...In a recruitment context and in relation to the richness of the food source, the foragers modulate the strength of their waggle dancing, the tempo of their visits to the food source, their likelihood of returning there (Seeley et al., 1991; Camazine and Sneyd, 1991), and the receptivity of the workers in the nest....

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Journal ArticleDOI
TL;DR: The selection of the path is shown to be a collective process whereby trail laying and following amplifies small initial differences in the traffic on each path caused by these three mechanisms, and the foragers show no significant tendency to follow the path they used previously.

431 citations


"Modulation of trail laying in the a..." refers background or methods or result in this paper

  • ...The results were less consistent for those ants going to the source, as many were making their first trip and thus did not lay trail pheromone (Beckers et al., 1992a)....

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  • ...An equivalent process can be seen in the collective selection of the shorter of two paths, in which L. niger foragers modulate their behavior as a function of their deviation from the nest-food axis (Beckers et al., 1992b)....

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  • ...MODEL OF TRAIL LAYING AND CHOICE OF SOURCE We use a model that reproduces the recruitment dynamics of L. niger, incorporating data from Beckers et al. (1992a) and from the experiments described above, to test how far the individual trail-laying and trail-following behavior can generate the overall…...

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  • ...If they did not start to lay trail on the first trip or subsequently stopped laying trail, then the probabilities that they start to lay trail (for the first time or again) are 0.1 and 0.05, respectively (Beckers et al., 1992a)....

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  • ...In detail, for a 1 M sugar source, the probabilities that a scout or a recruit start to lay trail for the first time, and also continue to lay trail on each subsequent trip, are 0.5 and 0.25, respectively, as measured by Beckers et al. (1992a)....

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Journal ArticleDOI
TL;DR: A series of experiments shows how the andLasius niger uses its trail recruitment system to select between two food sources, simultaneously presented with to 1M sucrose solution and when offered a 1M solution together with a 0.1M solution.
Abstract: A series of experiments shows how the andLasius niger uses its trail recruitment system to select between two food sources Simultaneously presented with to 1M sucrose solution it concentrates on one of them When offered a 1M solution together with a 01M solution it selects the richer source, unless the trait to the 01M source had become well-developed before the 1M source was introduced In the same situation, however, the group/mass recruiting antTetramorium caespitum uses its more individual transmission of information to switch to the 1M source A mathematical model describes these processes and its dynamics reflect the experimental results

332 citations


"Modulation of trail laying in the a..." refers background in this paper

  • ...taneously, the greater the proportion of trials in which the majority of the foragers exploited the 1 M source (confirming earlier results of Pasteels et al., 1987; Beckers et al., 1990)....

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  • ...In two earlier articles, we made a number of hypotheses to explain how colonies of trail-laying species, such as Tetramorium caespitum and Lasius niger (Pasteels et al., 1987; Beckers et al., 1990), select the richer of two sugar sources....

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  • ...…between the two sources introduced aA source was considered chosen if more than 60% of the ants went there. taneously, the greater the proportion of trials in which the majority of the foragers exploited the 1 M source (confirming earlier results of Pasteels et al., 1987; Beckers et al., 1990)....

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Journal ArticleDOI
TL;DR: In this article, the authors present a model that describes the honey bee colony's decision-making process, which consists of a system of non-linear differential equations describing the activity of the foraging bees.

249 citations