Abstract
Augmented reality (AR) tracking method allowed us not only to obtain entire interaction data but also entire behavioral big data, of ants, at the same time. Individual behavioral data may provide us a way to analyze individual personality behavioral responses to environmental condition, and an automatic way to detect their task allocation in a colony. In this study, individual behavioral differences were assessed by comparing individual behavior under normal and harsh environments, to evaluate individual responses. Individuals were classified based on their behavior; mobility patterns were analyzed to understand their relationship with respective network structure. These results show that individual behaviors are regulated as responses to environmental conditions and reactions differ depending on colony size. Individual classification and mobility patterns show that this method can be used to distinguish individuals solely by their behavioral and mobility patterns, which may have important roles in network structure pattern.
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This study was supported by JSPS KAKENHI Grant Number JP18J20064.
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Shoji, K. (2018). Individual Activity Level and Mobility Patterns of Ants Within Nest Site. In: Dorigo, M., Birattari, M., Blum, C., Christensen, A., Reina, A., Trianni, V. (eds) Swarm Intelligence. ANTS 2018. Lecture Notes in Computer Science(), vol 11172. Springer, Cham. https://doi.org/10.1007/978-3-030-00533-7_32
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DOI: https://doi.org/10.1007/978-3-030-00533-7_32
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