This paper surveys research on applying neuroevolution (NE) to games. In neuroevolution,
artificial neural networks are trained through evolutionary algorithms, taking inspiration from …

Georgios N. Yannakakis Julian Togelius Page 1 Artificial Intelligence and Games Georgios N.
Yannakakis Julian Togelius Page 2 Artificial Intelligence and Games Page 3 Georgios N …

This paper investigates the vision-based autonomous driving with deep learning and
reinforcement learning methods. Different from the end-to-end learning method, our method …

One way to approach end-to-end autonomous driving is to learn a policy function that maps
from a sensory input, such as an image frame from a front-facing camera, to a driving action …

This paper describes the 2009 Mario AI Competition, which was run in association with the
IEEE Games Innovation Conference and the IEEE Symposium on Computational …

One way to approach end-to-end autonomous driving is to learn a policy that maps from a
sensory input, such as an image frame from a front-facing camera, to a driving action, by …

We introduce a new reinforcement learning benchmark based on the classic platform game
Super Mario Bros. The benchmark has a high-dimensional input space, and achieving a …

We propose an end-to-end machine learning model that integrates multi-task (MT) learning,
convolutional neural networks (CNNs), and control algorithms to achieve efficient inference …

In modern racing games programming non-player characters with believable and
sophisticated behaviors is getting increasingly challenging. Recently, several works in the …

In this paper, we overview the 2009 Simulated Car Racing Championship-an event
comprising three competitions held in association with the 2009 IEEE Congress on …