9 citations · 9 across the 3 of their papers we have counts for
4 papers
Learning predictive representations in autonomous driving to improve deep reinforcement learning
Daniel Graves, Nhat M. Nguyen, Kimia Hassanzadeh +1
Reinforcement learning using a novel predictive representation is applied to autonomous driving to accomplish the task of driving between lane markings where substantial benefits i…
Perception as prediction using general value functions in autonomous driving applications
Daniel Graves, Kasra Rezaee, Sean Scheideman
We propose and demonstrate a framework called perception as prediction for autonomous driving that uses general value functions (GVFs) to learn predictions. Perception as predictio…
Efficient decorrelation of features using Gramian in Reinforcement Learning
Borislav Mavrin, Daniel Graves, Alan Chan
Learning good representations is a long standing problem in reinforcement learning (RL). One of the conventional ways to achieve this goal in the supervised setting is through regu…
Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning
Kristopher De Asis, Alan Chan, Silviu Pitis +2
We explore fixed-horizon temporal difference (TD) methods, reinforcement learning algorithms for a new kind of value function that predicts the sum of rewards over a $\textit{fixed…