Neuroevolutionary Multi-objective approaches to Trajectory Prediction in Autonomous Vehicles. (arXiv:2205.02105v1 [cs.NE])

The incentive for using Evolutionary Algorithms (EAs) for the automated
optimization and training of deep neural networks (DNNs), a process referred to
as neuroevolution, has gained momentum in recent years. The configuration and
training of these networks can be posed as optimization problems. Indeed, most
of the recent works on neuroevolution have focused their attention on
single-objective optimization. Moreover, from the little research that has been
done at the intersection of neuroevolution and evolutionary multi-objective
optimization (EMO), all the research …

arxiv autonomous autonomous vehicles prediction