5 citations · 10 across the 2 of their papers we have counts for
3 papers
Approximating Gradients for Differentiable Quality Diversity in Reinforcement Learning
Bryon Tjanaka, Matthew C. Fontaine, Julian Togelius +1
Consider the problem of training robustly capable agents. One approach is to generate a diverse collection of agent polices. Training can then be viewed as a quality diversity (QD)…
On the Importance of Environments in Human-Robot Coordination
Matthew C. Fontaine, Ya-Chuan Hsu, Yulun Zhang +2
When studying robots collaborating with humans, much of the focus has been on robot policies that coordinate fluently with human teammates in collaborative tasks. However, less emp…
Scalable Hierarchical Agglomerative Clustering
Nicholas Monath, Avinava Dubey, Guru Guruganesh +9
The applicability of agglomerative clustering, for inferring both hierarchical and flat clustering, is limited by its scalability. Existing scalable hierarchical clustering methods…