Simulating Species Interactions and Complex Emergence in Multiple Flocks of Boids with GPUS

Husselmann, Alwyn V.; Hawick, K. A.

doi:10.2316/p.2012.757-012

Cited by 7 publications

(9 citation statements)

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“…Some researchers reduced the computational workload by decreasing the update frequency (an increase in reaction time) of each individual, 21 others focused on the optimization or change of the perception and interaction system, [21][22][23][24] but as individual-based models are very suitable for parallel execution, many researchers adapted techniques from highly parallel processing. 21,23,25 The latter is most commonly achieved via general-purpose computing on graphics processing units (GPGPU). Unfortunately, if the simulation is to be used in a computer game, this kind of processing is not always available, with mobile games as the most known example-a vast majority of mobile phones at the time of this writing do not support GPGPU.…”

Section: Introductionmentioning

confidence: 99%

A hybrid model for simulating grazing herds in real time

Demšar

Blewitt

Bajec

2019

Computer Animation & Virtual

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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.

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Section: Introductionmentioning

confidence: 99%

A hybrid model for simulating grazing herds in real time

Demšar

Blewitt

Bajec

2019

Computer Animation & Virtual

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“…• Husselmann and Hawick (2011) add new species (predator) in the simulation to influence the starlings and their behaviors.…”

Section: Introductionmentioning

confidence: 99%

Complex flocking dynamics without global stimulus

Hermellin¹,

Michel²

2017

Proceedings of the 14th European Conference on Artificial Life ECAL 2017

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Murmuration, i.e. starlings gathering and swirling with extraordinary spatial coherence, is one of the most impressive kind of bird flocking. It is now well accepted that this collective behavior emerges from individual ones and that no global control is involved. In other words, every starling has an equivalent status in the flock and there is no leader deciding how the murmuration evolves. Considering this phenomenon, Reynolds' individual-based rules have been investigated and implemented a number of times to create compelling computer-animated models of the aerial movement of swarm-like flocks of starlings. Reynolds' model is considered as a classic Agent Based Model (ABM) and integrated as a flagship example in many ABM platforms.Still, it turns out that implementing Reynolds' model is not sufficient per se in the sense that all murmuration simulations use tricks to achieve a convincing animation of this phenomenon. Especially, virtual leaders or points of interest are used to orientate the starlings, which somehow contradicts the no-global-control perspective, and thus suggests that murmuration dynamics is not yet fully grasped. This paper first highlight this aspect of existing murmuration simulations and then show that it is possible to obtain murmuration-like dynamics by only rethinking how Reynolds' are usually implemented. Especially, the proposed model does not require the existence of a virtual leader nor embed any global aspect.The objective of this article is to show that it is possible to obtain complex coordinated flight dynamics using a very simple ABM and without adding external stimulus nor additional features, that is by only implementing Reynolds's rules thanks to the IRM4S modeling perspective (an Influence Reaction Model for Simulation). So, in this article, we will first focus on the existing implementations of flocking model to list the advantages and limits and then propose our solution based on the IRM4S approach.

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“…GPUs have already been used extensively in the literature for many fields of research including parametric evolutionary optimisers [1,18,36], machine learning [2], genetic programming [5,13,23,24] and agent-based modelling [19] among others. While GPU hardware provides for a potentially high performance platform, it also introduces several peculiarities due to the architecture, which was historically inspired from high-throughput processing of pixel data.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Individual Agent-based Simulation of Photobioreactors and Growth Control

Husselmann¹,

Hawick²

2013

Power and Energy / 807: Intelligent Systems and Control / 808: Technology for Education and Learning

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Photobioreactors offer an efficient and controllable environment from which many biomaterial-based products can be manufactured naturally. For example, the cultivation of the algae H. pluvialis, results in a carotenoid known as Astaxanthin, which is a highly valuable pigment and powerful antioxidant. The demand for naturally-produced Astaxanthin is much higher than synthetic, and the process by which this algae is cultivated is therefore important. We develop a discrete agent-based model that can be used to test the control processes for growing and harvesting such a bio product. We experiment with a variant of the Photosynthetic Factory model to improve cell division and hence growth kinetics. We employ parallel computing techniques to implement simulations of large numbers of control agents on graphical processing units. We discuss the implications of stochasticity, and propose a metric with which to balance cultivation time against fill rates of a stochastic data-parallel, bubble-column photobioreactor simulation.

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Simulating Species Interactions and Complex Emergence in Multiple Flocks of Boids with GPUS

Cited by 7 publications

References 0 publications

A hybrid model for simulating grazing herds in real time

A hybrid model for simulating grazing herds in real time

Complex flocking dynamics without global stimulus

Intelligent Individual Agent-based Simulation of Photobioreactors and Growth Control

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