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A mathematical model of foraging in a dynamic environment by trail-laying Argentine ants. (English) Zbl 1397.92765

Summary: Ants live in dynamically changing environments, where food sources become depleted and alternative sources appear. Yet most mathematical models of ant foraging assume that the ants’ foraging environment is static. Here we describe a mathematical model of ant foraging in a dynamic environment. Our model attempts to explain recent empirical data on dynamic foraging in the Argentine ant Linepithema humile (Mayr). The ants are able to find the shortest path in a Towers of Hanoi maze, a complex network containing 32,768 alternative paths, even when the maze is altered dynamically. We modify existing models developed to explain ant foraging in static environments, to elucidate what possible mechanisms allow the ants to quickly adapt to changes in their foraging environment. Our results suggest that navigation of individual ants based on a combination of one pheromone deposited during foraging and directional information enables the ants to adapt their foraging trails and recreates the experimental results.

MSC:

92D50 Animal behavior
92-04 Software, source code, etc. for problems pertaining to biology

Software:

Repast Suite
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[1] Aron, S.; Pasteels, J.M.; Deneubourg, J.-L., Trail-laying behaviour during exploratory recruitment in the argentine ant, iridomyrmex humilis (mayr), Biol. behav., 14, 207-217, (1989)
[2] Aron, S.; Beckers, R.; Deneubourg, J.-L.; Pasteels, J.M., Memory and chemical communication in the orientation of two mass-recruiting ant species, Insectes soc., 40, 369-380, (1993)
[3] Beckers, R.; Deneubourg, J.-L.; Goss, S., Trails and u-turns in the selection of a path by the ant lasius niger, J. theor. biol., 159, 397-415, (1992)
[4] Beekman, M.; Dussutour, A., How to tell your mates—costs and benefits of different recruitment mechanisms, (), 105-124
[5] de Melo, E.B.B., Araujo, A.F.R., 2008. Modeling ant colony foraging in dynamic and confined environment. In: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation.; de Melo, E.B.B., Araujo, A.F.R., 2008. Modeling ant colony foraging in dynamic and confined environment. In: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation.
[6] de Melo, E.B.B.; Araujo, A.F.R., Modeling ant colony foraging in a dynamic and confined environment, Biosystems, 104, 23-31, (2011)
[7] Deneubourg, J.-L.; Aron, S., Random behaviour, amplification processes and number of participants: how they contribute to the foraging properties of ants, Phys. D, 22, 176-186, (1986)
[8] Deneubourg, J.-L.; Aron, S.J.; Goss, S.; Pasteels, J.M., The self-organizing exploratory pattern of the argentine ant, J. insect behav., 3, 159-168, (1990)
[9] Dussutour, A.; Deneubourg, J.-L.; Fourcassie, V., Amplification of individual preferences in a social context: the case of wall-following in ants, Proc. R. soc. B, 272, 705-714, (2005)
[10] Dussutour, A.; Beekman, M.; Nicolis, S.C.; Meyer, B., Noise improves collective decision-making by ants in dynamic environments, Proc. R. soc. B, 276, 4353-4361, (2009)
[11] Dussutour, A.; Nicolis, S.C.; Shephard, G.; Beekman, M.; Sumpter, D.J.T., The role of multiple pheromones in food recruitment by ants, J. exp. biol., 212, 2337-2348, (2009)
[12] Garnier, S.; Guerecheau, A.; Combe, M.; Fourcassie, V.; Theraulaz, G., Path selection and foraging efficiency in argentine ant transport networks, Behav. ecol. sociobiol., 63, 1167-1179, (2009)
[13] Gerbier, G.; Garnier, S.; Rieu, C.; Theraulaz, G.; Fourcassie, V., Are ants sensitive to the geometry of tunnel bifurcation?, Anim. cognit., 11, 637-642, (2008)
[14] Goss, S.; Aron, S.; Deneubourg, J.-L.; Pasteels, J.M., Self-organized shortcuts in the argentine ant, Naturwissentschaften, 76, 579-581, (1989)
[15] King, A.J.; Cowlishaw, G., When to use social information: the advantage of large group size in individual decision making, Biol. lett., 3, 137-139, (2007)
[16] Lachmann, M.; Sella, G.; Jablonka, E., On the advantages of information sharing, Proc. R. soc. lond. B, 267, 1287-1293, (2000)
[17] North, M.; Collier, N.; Vos, J., Experiences creating three implementations of the repast agent modeling toolkit, ACM trans. model. comput. simul., 16, 1-25, (2006)
[18] Reid, C.R.; Sumpter, D.J.T.; Beekman, M., Optimisation in a natural system: argentine ants solve the towers of Hanoi, J. exp. biol., 214, 50-58, (2011)
[19] Robinson, E.J.H.; Jackson, D.E.; Holcombe, M.; Ratnieks, F.L.W., ‘no entry’ signal in ant foraging, Nature, 438, 442, (2005)
[20] Schweitzer, F.; Lao, K.; Family, F., Active random walkers simulate trunk trail formation by ants, Biosystems, 41, 153-166, (1997)
[21] Vela-Perez, M., Fontelos, M.A., Velazquez, J.J.L., 2011. Ant foraging and minimal paths in simple graphs. ArXiv:1103.1612v1; Vela-Perez, M., Fontelos, M.A., Velazquez, J.J.L., 2011. Ant foraging and minimal paths in simple graphs. ArXiv:1103.1612v1
[22] Vittori, K., Gautrais, J., Araujo, A.F., Fourcassie, V., Theraulaz, G., 2004. Modeling ant behavior under a variable environment. In: Lecture Notes in Computer Science, vol. 3172, pp. 190-201.; Vittori, K., Gautrais, J., Araujo, A.F., Fourcassie, V., Theraulaz, G., 2004. Modeling ant behavior under a variable environment. In: Lecture Notes in Computer Science, vol. 3172, pp. 190-201.
[23] Vittori, K.; Talbot, G.; Gautrais, J.; Fourcassie, V., Path efficiency of ant foraging trails in an artificial network, J. theor. biol., 239, 507-515, (2006) · Zbl 1445.92305
[24] van Vorhis Key, S.E.; Baker, T.C., Observations on the trail deposition and recruitment behaviors of the argentine ant, iridomyrmex humilis (hymenoptera: formicidae), Ann. entomol. soc. am., 79, 283-288, (1986)
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