Graham Quee

Space-use Animal Behaviour Using a Cognitive Movement Model

Predicting movement patterns in cognitive animals is limited by our inability to understand the underlying thought process it depends on. Yet movement is fundamental to the utilization of most organism’s environment, and thus is of significant interest to ecological study. This talk will provide an overview for a very general framework by Tal Avgar et al. for modelling how an animal perceives objects in it’s environment, and how this information affects the movement patterns. The model is a discrete space and time algorithm which employs a basic machine learning scheme resulting in probabilistic movement at each step on a hexagonal tiling of the landscape. Applications of the model in determining how altering objects in the landscape change the space-use behaviour of the animal will also be discussed.