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AgentScapes-Designing Water Efficient Landscapes Using Distributed Agent-based Optimization

机译:使用基于分布式代理的优化设计验光CAPES设计水有效景观

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In arid and semi-arid regions, landscaping can reduce the energy use of a home and generate a more pleasing environment for the home's residents. However, water in these regions is a scarce resource, which makes landscaping a tradeoff between conflicting objectives-maximizing the growth on the landscape while minimizing the water use. This paper presents a new system, called AgentScapes, that uses agent-based modelling and distributed optimization to design water-conserving residential landscapes. The agent-based model included in AgentScapes combines the basic ideas of local search and the specifics of how plant communities emerge based on individual plant-plant interactions and responses to resources available on the landscape. Agents in this model are plants with different light and water requirements placed on a simulated landscape with specified light and water conditions. Individual plant agents in desirable locations survive, while struggling agents die off and re-emerge in a new location. These interactions enable each plant agent to search for a location that maximizes its growth and minimizes its water use. The agent-based model generates solutions that are within 95 percent of optimal in a fraction of the time required for exhaustive search solutions. In addition, the agent model is able to reproduce heuristics for low-water garden design and present a new option for reducing water use.
机译:在干旱和半干旱地区,景观可以减少房屋的能源使用,为家庭居民提供更令人愉悦的环境。然而,这些地区的水是一种稀缺的资源,这使得突出的目标之间的兴奋 - 最大限度地提高景观的增长,同时最小化水量。本文介绍了一个名为AgentsCap的新系统,它使用基于代理的建模和分布式优化来设计水保存的住宅景观。 AgentsCapes中包括的基于代理的模型结合了本地搜索的基本思想和植物社区如何基于个体植物植物的相互作用以及对景观中可用资源的响应来出现的具体细节。该模型中的代理是具有不同光线和水需求的植物,在模拟景观中,具有特定的光线和水条件。在理想的地点的个体植物代理生存,而挣扎的药剂在新的位置死亡并重新出现。这些相互作用使每个工厂代理能够搜索最大化其生长并最大限度地减少其用水的位置。基于代理的模型在穷举搜索解决方案所需的时间一小部分中产生的解决方案在最佳状态中。此外,代理模型能够再现低水园设计的启发式,并提出了降低水的新选择。

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