Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires
Bryan Lim,Luca Grillotti,Lorenzo Bernasconi,Antoine Cully,Bryan Lim,Luca Grillotti,Lorenzo Bernasconi,Antoine Cully
Quality-Diversity (QD) algorithms are powerful exploration algorithms that allow robots to discover large repertoires of diverse and high-performing skills. However, QD algorithms are sample inefficient and require millions of evaluations. In this paper, we propose Dynamics-Aware Quality-Diversity (DA-QD), a framework to improve the sample efficiency of QD algorithms through the use of dynamics mo...
