9 citations · 22 across the 11 of their papers we have counts for
5 papers · 1 filter
A Simple Decentralized Cross-Entropy Method
Zichen Zhang, Jun Jin, Martin Jagersand +2
Cross-Entropy Method (CEM) is commonly used for planning in model-based reinforcement learning (MBRL) where a centralized approach is typically utilized to update the sampling dist…
Dynamic Decision Frequency with Continuous Options
Amirmohammad Karimi, Jun Jin, Jun Luo +3
In classic reinforcement learning algorithms, agents make decisions at discrete and fixed time intervals. The duration between decisions becomes a crucial hyperparameter, as settin…
Build generally reusable agent-environment interaction models
Jun Jin, Hongming Zhang, Jun Luo
This paper tackles the problem of how to pre-train a model and make it generally reusable backbones for downstream task learning. In pre-training, we propose a method that builds a…
What makes useful auxiliary tasks in reinforcement learning: investigating the effect of the target policy
Banafsheh Rafiee, Jun Jin, Jun Luo +1
Auxiliary tasks have been argued to be useful for representation learning in reinforcement learning. Although many auxiliary tasks have been empirically shown to be effective for a…
Generalizable task representation learning from human demonstration videos: a geometric approach
Jun Jin, Martin Jagersand
We study the problem of generalizable task learning from human demonstration videos without extra training on the robot or pre-recorded robot motions. Given a set of human demonstr…