Determining interaction rules in animal swarms
Journal article, 2010

In this paper, we introduce a method for determining local interaction rules in animal swarms. The method is based on the assumption that the behavior of individuals in a swarm can be treated as a set of mechanistic rules. The principal idea behind the technique is to vary parameters that define a set of hypothetical interactions, as for example, a rule for aligning with neighbors. The parameter values are optimized so that the deviation between the observed movements in an animal swarm and the movements predicted by the assumed rule set is minimal. We demonstrate the method by reconstructing the interaction rules from the trajectories produced by a computer simulation.

behavioral rules

movement

tools

force matching

reverse engineering

fish

selfish herd

memory

flocks

collective behavior

model

swarming

Author

A. Eriksson

University of Cambridge

Martin Nilsson Jacobi

Princeton University

J. Nystrom

Princeton University

Kolbjörn Tunström

Chalmers, Energy and Environment, Physical Resource Theory

Behavioral Ecology

1045-2249 (ISSN) 1465-7279 (eISSN)

Vol. 21 5 1106-1111

Subject Categories

Biological Sciences

DOI

10.1093/beheco/arq118

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5/2/2018 7