In this paper, we applied online neuroevolution to evolve nonplayer characters for The Open Racing Car Simulator (TORCS). While previous approaches allowed online learning with per...
Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
Many ensemble methods, such as Bagging, Boosting, Random Forest, etc, have been proposed and widely used in real world applications. Some of them are better than others on noisefre...
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
This paper is about constructing confidence bands around ROC curves. We first introduce to the machine learning community three band-generating methods from the medical field, and...
Sofus A. Macskassy, Foster J. Provost, Saharon Ros...