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Isaac Rudomin
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Proceedings Papers
. alif2016, ALIFE 2016, the Fifteenth International Conference on the Synthesis and Simulation of Living Systems638-645, (July 4–6, 2016) 10.1162/978-0-262-33936-0-ch102
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Microscopic crowd simulation usually uses ad-hoc models. While these have been proven to be useful, they are difficult to calibrate and do not always reflect real behaviour. For this reason we propose a machine learning approach using neural networks. The main contribution of the project is a first exploration of prediction of agent trajectories using two specific types of neural networks, Support Vector Machine (SVM) and Spiking Neural Networks (SNN).