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A hybrid model for simulating grazing herds in real time
Computer Animation and Virtual Worlds ( IF 0.9 ) Pub Date : 2019-08-08 , DOI: 10.1002/cav.1914
Jure Demšar 1 , Will Blewitt 2 , Iztok Lebar Bajec 1
Affiliation  

Computer simulations of animal groups are usually performed via individual‐based modelling, where simulated animals are designed on the level of individuals. With this approach, developers are able to capture behavioural nuances of real animals. However, modelling each individual as its own entity has the downside of having a high computational cost, meaning that individual‐based models are usually not suitable for real‐time simulations of very large groups. A common alternative approach is flow‐based modelling, where the dynamics of animal congregations are designed on the group level. This enables researchers to create real‐time simulations of massive phenomena at the cost of biological authenticity. A novel approach called hybrid modelling tries to mix the best of both worlds—precision of individual‐based models and speed of flow‐based ones. An unknown surrounding hybrid model is the question of their biological authenticity and relevance. In this study, we develop a hybrid model for the simulation of herds of grazing sheep. Through Bayesian data analysis, we show that such an approach can encompass several aspects of real‐world sheep behaviour. Our hybrid model is also extremely efficient, capable of simulating herds of more than 1,000 individuals in real time without resorting to graphics processing unit execution.

中文翻译:

用于实时模拟放牧群的混合模型

动物群体的计算机模拟通常通过基于个体的建模进行,其中模拟动物是在个体水平上设计的。通过这种方法,开发人员能够捕捉真实动物的行为细微差别。然而,将每个个体建模为自己的实体具有计算成本高的缺点,这意味着基于个体的模型通常不适合对非常大的群体进行实时模拟。一种常见的替代方法是基于流的建模,其中动物群的动态是在群体层面设计的。这使研究人员能够以生物真实性为代价创建大规模现象的实时模拟。一种称为混合建模的新方法试图混合两全其美——基于个体的模型的精度和基于流的模型的速度。一个未知的周围混合模型是其生物学真实性和相关性的问题。在这项研究中,我们开发了一个用于模拟放牧羊群的混合模型。通过贝叶斯数据分析,我们表明这种方法可以涵盖现实世界绵羊行为的几个方面。我们的混合模型也非常高效,能够实时模拟超过 1,000 人的牛群,而无需求助于图形处理单元执行。
更新日期:2019-08-08
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