most citedEfficient Exploration through Intrinsic Motivation Learning for Unsupervised Subgoal Discovery in Model-Free Hierarchical Reinforcement Learning

2 citations · 2 across the 1 of their papers we have counts for

collaborators

3 papers

cs.LG2019★ 2 cited

Efficient Exploration through Intrinsic Motivation Learning for Unsupervised Subgoal Discovery in Model-Free Hierarchical Reinforcement Learning

Jacob Rafati, David C. Noelle

Efficient exploration for automatic subgoal discovery is a challenging problem in Hierarchical Reinforcement Learning (HRL). In this paper, we show that intrinsic motivation learni…

cs.LG2019

Quasi-Newton Optimization Methods For Deep Learning Applications

Jacob Rafati, Roummel F. Marcia

Deep learning algorithms often require solving a highly non-linear and nonconvex unconstrained optimization problem. Methods for solving optimization problems in large-scale machin…

cs.LG2019

Learning sparse representations in reinforcement learning

Jacob Rafati, David C. Noelle

Reinforcement learning (RL) algorithms allow artificial agents to improve their selection of actions to increase rewarding experiences in their environments. Temporal Difference (T…