| This work investigates effective search and resource collection algorithms for swarms. Deterministic spiral algorithms and Levy search processes have been shown to be optimal for single searchers. By generalising these approaches to swarms and measuring the effectiveness of the resulting search patterns in computer models, we find that the intensity-extent trade-off, formalised as the fractal dimension of the search pattern, can be used to adapt search to common challenges in swarm search.;Search extent and intensity lie on a continuum: more intensive patterns search thoroughly in the local area, while extensive patterns cover more area but may miss targets nearby. We show that the most efficient trade-off between search intensity and extent for swarms depends strongly on the distribution of targets, swarm size and the rate of collision among searchers (Fricke et al., 2016a). The optimal trade-off is also influenced by the target detection error rate. The search can, therefore, be tuned to match conditions common in real-world robot search tasks.;We also demonstrate that our swarm spiral algorithm is an effective strategy for resource collection (Fricke et al., 2016b). Deterministic spiral search strategies for single searchers have been considered unsuitable in the presence of localisation error (Reynolds et al., 2007), but the swarm algorithm performs well even in the presence of localisation error. Since the spiral strategy is effective and easily analysed it makes an ideal benchmark against which to compare stochastic search processes.;Collective search by T cells is a critical component of the adaptive immune response. We characterise T cell search patterns and find that they balance the need to search extensively for rare antigen while maintaining local contacts with antigen-presenting cells. We perform two analyses that demonstrate that T cells interact with their environment during search. We also measure the interaction between T cells and Dendritic cells using mutual information and demonstrate non-random spatial association between T cells and their targets. |
