Mobile Cellular Automata Models of Ant Behavior: Movement Activity of Leptothorax allardycei

Mobile cellular automata (MCA) models of the activity of ant colonies were used to explore the effects of changing the parameters that govern the types of interactions that can occur between ants. Two parameters have an effect: whether interactions between active ants influence each other's activity and whether interactions between active and inactive ants influence the activity of the inactive ants We then investigated the production of periodic activity in artificial aggregates of workers of Leptothorax allardycei. Using an automated data collection system to analyze the activity patterns of 126 data records of 11.5 h each, we studied the effects of three attributes on the production of periodic activity: the size of the aggregate, the time of day, and the presence of the brood. When the brood was absent, the size of the aggregate had a significant effect on the production of periodic patterns of activity; however, this effect was most pronounced during the day and nearly absent in data records obtained at night. When the brood was present, the time of day had no effect, and the effect of aggregate size was much more pronounced; the extent of periodicity increased linearly with the size of the aggregate All of the experimental results could be reclaimed by altering the parameters of the MCA models. Mobile cellular automata models produce testable predictions that make them especially useful for models of animal behavior.

[1]  M. Nowak,et al.  Evolutionary games and spatial chaos , 1992, Nature.

[2]  Ricard V. Solé,et al.  Collective behavior of random-activated mobile cellular automata , 1993 .

[3]  M. Elgar,et al.  PREDATOR VIGILANCE AND GROUP SIZE IN MAMMALS AND BIRDS: A CRITICAL REVIEW OF THE EMPIRICAL EVIDENCE , 1989, Biological reviews of the Cambridge Philosophical Society.

[4]  M. Wade,et al.  Selection Within and between Kin Groups of the Imported Willow Leaf Beetle , 1989, The American Naturalist.

[5]  Nigel R. Franks,et al.  Synchronization of the behaviour within nests of the ant Leptothorax acervorum (fabricius)—I. Discovering the phenomenon and its relation to the level of starvation , 1990 .

[6]  G. Rose,et al.  Cod spawning on a migration highway in the north-west Atlantic , 1993, Nature.

[7]  J. Gerard,et al.  From individual to collective vigilance in wild boar (Sus scrofa) , 1992 .

[8]  Chris Tofts,et al.  The autosynchronization of the ant Leptothorax acervorum (Fabricius) : theory, testability and experiment , 1992 .

[9]  Nigel R. Franks,et al.  Synchronization of the behaviour within nests of the antLeptothorax acervorum (Fabricius)—II. Modelling the phenomenon and predictions from the model , 1990 .

[10]  A. Ōkubo Dynamical aspects of animal grouping: swarms, schools, flocks, and herds. , 1986, Advances in biophysics.

[11]  G B Ermentrout,et al.  Cellular automata approaches to biological modeling. , 1993, Journal of theoretical biology.

[12]  B. Goodwin,et al.  A Parallel Distributed Model of the Behaviour of Ant Colonies , 1992 .

[13]  B. Silverman,et al.  Self-organizing nest construction in ants: sophisticated building by blind bulldozing , 1992, Animal Behaviour.

[14]  B. Cole Is animal behaviour chaotic? Evidence from the activity of ants , 1991, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[15]  J. Deneubourg,et al.  Collective patterns and decision-making , 1989 .

[16]  H. Reeve Queen activation of lazy workers in colonies of the eusocial naked mole-rat , 1992, Nature.

[17]  Ricard V. Solé,et al.  Oscillations and Chaos in Ant Societies , 1993 .

[18]  Jane Molofsky,et al.  POPULATION DYNAMICS AND PATTERN FORMATION IN THEORETICAL POPULATIONS , 1994 .