Javascript must be enabled for the correct page display

Simulating the influence of lateralized reactions in schooling fish

Nauta, J.C. (2015) Simulating the influence of lateralized reactions in schooling fish. Master's Thesis / Essay, Computing Science.

thesis_JelleNauta_v7_2_2.pdf - Published Version

Download (4MB) | Preview
[img] Text
Toestemming.pdf - Other
Restricted to Backend only

Download (222kB)


In this Master's thesis, the influence of behavioral lateralization in schooling fish is studied using an agent-based simulation. For this, we wrote a tool in C++ and GLSL for 3D simulations, with emphasis on extensibility and speed. The fish in our simulations are lateralized by letting them respond more strongly to neighbors on their left than on their right, or vice versa. We first study the behavior of our model without lateralization for school sizes of up to 2000 individuals, and compare these to simulation efforts from the literature. We then study the influence of individual lateralization strength, and of mixing individuals of opposite lateralization in the same school, in schools of 200 simulated fish. Schooling behavior is evaluated using a number of metrics such as nearest neighbor distance, school volume, turning rate and school speed. The most important feature of a lateralized fish in our model is that it has a preferential turning direction (left or right) while schooling. In schools consisting of fish with opposite lateralization directions, this turning preference leads to assortment of fish by their lateralization direction. In schools with unequal fractions of opposite lateralization, we find that the school has a turning bias. This bias leads to several non-monotonic dependencies of our metrics with respect to the ratio of fish with different lateralization types. These non-monotonic dependencies demonstrate that interactions between neighbors in a school may lead to schools that are composed of different numbers of left- and right-lateralized individuals, as observed in nature.

Item Type: Thesis (Master's Thesis / Essay)
Degree programme: Computing Science
Thesis type: Master's Thesis / Essay
Language: English
Date Deposited: 15 Feb 2018 08:09
Last Modified: 15 Feb 2018 08:09

Actions (login required)

View Item View Item