Building models : developing the behavioural model of Temnothorax collective wall building to study the evolutionary robustness of self-organised algorithms

  • Edith Invernizzi

Student thesis: Doctoral Thesis (PhD)


This thesis focuses on wall building behaviour in Temnothorax ants as a case study of self-organised collective behaviour. It contains a progressing series of research packages, building towards one evolutionary question: how eusocial insect nest building algorithms successfully make the transition between two rule variants. I start by revising the existent behavioural model of Temnothorax wall building. By replicating the original agent-based model, I identify two issues: 1. the behavioural model performs poorly in conditions of low building material availability; and 2. the behavioural model lacks behavioural termination. I then introduce a revised version of the behavioural model (the gradual model) in which high stone density at building sites triggers a decrease in building activity, eventually leading to behavioural termination. I then compare the fit of both models to empirical data using laboratory observations of T. rugatulus wall building, applying a hidden Markov model framework to interpret the data. The gradual model provides the best match to the observed data. Finally, I use the revised model to test, in an agent-based model setting, how wall quality responds to different types of inter-worker variation in the building rule used: the presence of a mutant variant spreading within the colony; the co-existence of multiple variants; and widespread epigenetic individual variation. I find wall quality to be very robust to nearly any degree and frequency of variants. With additional simulations, I identify the two key elements of the building algorithm that provide robustness: the positive feedback effect, co-localising worker effort despite starting individual variation; and the existence of an area of overlap where activity occurs with high frequency under all variants (a buffer zone). I predict that these two components have been under selection for evolvability in wall building Temnothorax ants.
Date of Award29 Nov 2022
Original languageEnglish
Awarding Institution
  • University of St Andrews
SupervisorGraeme Douglas Ruxton (Supervisor) & V Anne Smith (Supervisor)


  • Group behaviour
  • Self-organisation
  • Ant
  • Temnothorax
  • Nest building
  • Evolution
  • Evolution of collective behaviour
  • Evolution and self-organisation

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