This important study uses reinforcement learning to study how turbulent odor stimuli should be processed to yield successful navigation. The authors find that there is an optimal memory length over ...

Chicago Cubs president of baseball operations Jed Hoyer keeps getting the same message from rival officials as he collects information ahead of the July 31 trade deadline: We’re going to wait and see ...

Abstract: In this paper, Q-learning and Double Q-learning reinforcement learning algorithms were used to fine-tune sliding mode controller parameters to balance the Ball-and-Beam system. Each ...

Institute of Logistics Science and Engineering of Shanghai Maritime University, Pudong, China Introduction: This study addresses the joint scheduling optimization of continuous berths and quay cranes ...

Abstract: This paper focuses on solving the linear quadratic regulator problem for discrete-time linear systems without knowing system matrices. The classical Q-learning methods for linear systems can ...

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

This example shows how to build and train a convolutional neural network (CNN) from scratch to perform a classification task with an EEG dataset.