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Use of machine learning techniques to model wind damage to forests

Journal Article
Hart, E., Sim, K., Kamimura, K., Meredieu, C., Guyon, D., & Gardiner, B. (2019)
Use of machine learning techniques to model wind damage to forests. Agricultural and forest meteorology, 265, 16-29. https://doi.org/10.1016/j.agrformet.2018.10.022
This paper tested the ability of machine learning techniques, namely artificial neural networks and random forests, to predict the individual trees within a forest most at r...

Emergence of hierarchy from the evolution of individual influence in an agent-based model

Conference Proceeding
Perret, C., Powers, S. T., & Hart, E. (2017)
Emergence of hierarchy from the evolution of individual influence in an agent-based model. In Proceedings of the 14th European Conference on Artificial Life 2017, (348-355
The sudden transition from egalitarian groups to hierarchical societies that occurred with the origin of agriculture is one of the most striking features of the evolution of h...

Collaborative Diffusion on the GPU for Path-Finding in Games

Conference Proceeding
McMillan, C., Hart, E., & Chalmers, K. (2015)
Collaborative Diffusion on the GPU for Path-Finding in Games. In A. M. Mora, & G. Squillero (Eds.), Applications of Evolutionary Computation; Lecture Notes in Computer Science, (418-429). https://doi.org/10.1007/978-3-319-16549-3_34
Exploiting the powerful processing power available on the GPU in many machines, we investigate the performance of parallelised versions of pathfinding algorithms in typical ga...