103 citations · 124 across the 7 of their papers we have counts for
4 papers · 1 filter
LISPR: An Options Framework for Policy Reuse with Reinforcement Learning
Daniel Graves, Jun Jin, Jun Luo
We propose a framework for transferring any existing policy from a potentially unknown source MDP to a target MDP. This framework (1) enables reuse in the target domain of any form…
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…
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…