4 citations · 6 across the 4 of their papers we have counts for
4 papers
dpvis: A Visual and Interactive Learning Tool for Dynamic Programming
David H. Lee, Aditya Prasad, Ramiro Deo-Campo Vuong +3
Dynamic programming (DP) is a fundamental and powerful algorithmic paradigm taught in most undergraduate (and many graduate) algorithms classes. DP problems are challenging for man…
Density Descent for Diversity Optimization
David H. Lee, Anishalakshmi V. Palaparthi, Matthew C. Fontaine +2
Diversity optimization seeks to discover a set of solutions that elicit diverse features. Prior work has proposed Novelty Search (NS), which, given a current set of solutions, seek…
pyribs: A Bare-Bones Python Library for Quality Diversity Optimization
Bryon Tjanaka, Matthew C. Fontaine, David H. Lee +6
Recent years have seen a rise in the popularity of quality diversity (QD) optimization, a branch of optimization that seeks to find a collection of diverse, high-performing solutio…
Training Diverse High-Dimensional Controllers by Scaling Covariance Matrix Adaptation MAP-Annealing
Bryon Tjanaka, Matthew C. Fontaine, David H. Lee +2
Pre-training a diverse set of neural network controllers in simulation has enabled robots to adapt online to damage in robot locomotion tasks. However, finding diverse, high-perfor…