Modeling and Analysis of Fish Interaction Networks under Projected Visual Stimuli
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866918368612712448 |
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| author | Kawashima, Hiroaki Malinda, Raj Rajeshwar Takizawa, Saeko |
| author_facet | Kawashima, Hiroaki Malinda, Raj Rajeshwar Takizawa, Saeko |
| contents | This paper addresses the estimation of a dynamic interaction network, a network of influence among individuals, under projected visual stimuli to quantify the influences of inter-individual interactions and external stimuli on collective behavior. Building upon our previously proposed network estimation model, which assumes a Boids-type model and employs a sparse regression framework to infer inter-individual influence networks from trajectory data, we extend the formulation by introducing a stimulus term. This enables the model to capture how individuals react to and propagate externally projected visual stimuli within the group. The resulting framework allows simultaneous estimation of inter-individual and stimulus-related interaction strengths. We also introduce entropy-based indices to capture the possible biases of individuals' influence. Our experiments with fish schools under projector-based visual stimuli demonstrate the effectiveness of the proposed indices in quantifying schooling behavior and identifying influential individuals within the group, serving as the basis for real-time, interpretable metrics of collective dynamics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_01682 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Modeling and Analysis of Fish Interaction Networks under Projected Visual Stimuli Kawashima, Hiroaki Malinda, Raj Rajeshwar Takizawa, Saeko Social and Information Networks Quantitative Methods This paper addresses the estimation of a dynamic interaction network, a network of influence among individuals, under projected visual stimuli to quantify the influences of inter-individual interactions and external stimuli on collective behavior. Building upon our previously proposed network estimation model, which assumes a Boids-type model and employs a sparse regression framework to infer inter-individual influence networks from trajectory data, we extend the formulation by introducing a stimulus term. This enables the model to capture how individuals react to and propagate externally projected visual stimuli within the group. The resulting framework allows simultaneous estimation of inter-individual and stimulus-related interaction strengths. We also introduce entropy-based indices to capture the possible biases of individuals' influence. Our experiments with fish schools under projector-based visual stimuli demonstrate the effectiveness of the proposed indices in quantifying schooling behavior and identifying influential individuals within the group, serving as the basis for real-time, interpretable metrics of collective dynamics. |
| title | Modeling and Analysis of Fish Interaction Networks under Projected Visual Stimuli |
| topic | Social and Information Networks Quantitative Methods |
| url | https://arxiv.org/abs/2603.01682 |