Date: March 13th 2017 at 4:00pm
Location: Rm 4421, The CS Thesis Room
Presenter: Thomas Flynn
The topology of artificial neural networks has typically been designed by human engineering, but there exists the potential for discovering better network topologies through automated search. Genetic algorithms give a biologically plausible method for starting with a minimally viable network and evolving its topology to accomplish a given task. This week we’ll be looking at MarI/O, an implementation of NeuroEvolution of Augmenting Topologies, for beating a level of the popular video game Super Mario Brothers 3 which is known to be an NP-Hard game.
