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Chapter 9: Complicated Behavior
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Animal groups aren't just complex, they can also be complicated! Individual honey bees are known to use at least 17 different 22 communication signals, the most famous of which is the waggle dance, and adjust their 23 behaviour in response to at least 34 different cues. The bees take different 24 behavioural roles at different times during their life. Furthermore, there are certain components, 25 such as the queen, which are essential to the smooth functioning of the colony. Here I look at models that attempt to capture more fully the detailed interactions within insect societies. The chapterintroduces the use of state- and agent-based models, using foraging and emigration of social insects as case studies around which the various techniques are discussed.

Key ideas covered in this chapter: behavioural state modelling; complicated individuals; differential equation models; agent and individual based models; emigration of Temnothorax ants and honey bees; algorithm analysis and robustness; formalising individual-based models; process algebras; dimension reduction.

Links

Claire Detrain's homepage

Stephen Pratt's homepage

Chris Tofts's homepage

Jennifer Fewell's homepage

Nigel Franks's homepage

 

References

Biesmeijer, J. C. & de Vries, H. 2001. Exploration and exploitation of food sources by social insect colonies: a revision of the scout-recruit concept. Behavioral Ecology and Sociobiology, 49, 89-99.

Detrain, C. & Deneubourg, J. L. 2002. Complexity of environment and parsimony of decision rules in insect societies. Biological Bulletin, 202, 268-274.

Fewell, J. H. 2003. Social insect networks. Science, 301, 1867-1870.

Goldenfeld, N. & Kadanoff, L. P. 1999. Simple Lessons from Complexity. Science, 284, 87-89.

Kitano, H. 2002. Computational systems biology. Nature (London), 420.

Pratt, S. C., Sumpter, D. J. T., Mallon, E. B. & Franks, N. R. 2005. An agent-based model of collective nest choice by the ant Temnothorax albipennis. Animal Behaviour, 70, 1023-1036.

Pratt, S. C. & Sumpter, D. J. T. 2006. A tunable algorithm for collective decision-making. Proceedings of the National Academy of Sciences of the United States of America, 103, 15906-15910.

Seeley, T. D. 2002. When is self-organization used in biological systems? Biological Bulletin, 202, 314-318.

Sumpter, D. J. T. 2006. The principles of collective animal behaviour. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences, 361, 5-22.

Tofts, C. M. 1994. Processes with probabilities, priorities and time. Formal Aspects of Computer Science, 6, 536-564.

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