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An agent based modeling approach to explain the perception of environmental stressors

机译:基于主体的建模方法来解释环境压力源的感知

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Artificial intelligence traditionally draws inspiration from biological systems, in order to achieve a similar degree of intelligence in artificial systems. More recently, ideas from computational intelligence are being applied successfully in achieving a better understanding of the mechanisms underlying the emergence of group-level patterns in biological and sociological systems. In this paper, the use of an intelligent software agent for mimicking the human response to environmental stressors is proposed. The conceptual model for a single individual contains strongly interacting submodels for sensory observation of the environment, cognition and emotion. A partial implementation of this model, focused on auditory perception, is applied to gain additional insight in the underlying mechanisms that lead to the emergence of noise annoyance at the community level. In particular, it is shown that this new approach may give a possible explanation for the difference in annoyance between road and railway traffic for equal sound level, as is observed in numerous noise surveys and laboratory experiments.
机译:传统上,人工智能从生物系统中汲取灵感,以便在人工智能系统中获得类似程度的智能。最近,来自计算智能的思想被成功地用于更好地理解生物学和社会学系统中群体级模式出现的机制。在本文中,提出了使用智能软件代理来模仿人类对环境压力源的响应。一个人的概念模型包含相互作用强烈的子模型,用于对环境,认知和情感的感官观察。该模型的一部分实现(侧重于听觉感知)被应用来获得对导致社区中噪声烦恼出现的潜在机制的更多了解。尤其是,它表明,这种新方法可能为相同声级的公路和铁路交通之间的烦恼差异提供了可能的解释,正如在众多噪声调查和实验室实验中所观察到的那样。

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