Automated Extraction of Movement Rationales (Sengupta et al., 2018)

In this paper, the authors present the rationale of animal movements, and show how to extract “rules” from movement data by applying agent-based models (ABMs).

To understand the movement of individual organism, the authors refer to four components including internal state, motion capacity, navigation capacity and external factors, which proposed by Nathan et al. (2008). However, the authors admit that the internal state data are not easy to capture, and they actually didn’t use these data in the experiment. Nevertheless, I believe internal state might influence the modelling results to certain extents. I suppose the movement of animals can reduced by illness or feelings of individuals. It may or may not be significant factors, but it is still an issue that should not be overlooked. As we know, ABMs are not only applied to animal movements, they also used to discover pattern in human activities and support decisions. You cannot deny the importance of individual feelings, wills or other internal elements for concerns of social justice. Even this adds much more complexity when applying models, there is still a necessity to do so when involve humans.

Back to the animal movements, the sample data is gathered from Red Colobus from a national park. The authors infer that there is no mating and predation involved. However, it is not an usual situation in the wild world. I may regard this model as a relative simple version for testing the movement rationale, but not think it is a mature one since the applied scene is kind of ideal. While, I credit the thought to break down the rationales into movement itself and environmental factors. It is a reasonable way to simplify a complicate situation with rigors.

Comments are closed.