An Agent Based Modeling Approach to Explain the Perception of Environmental Stressors

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.