963 citations · 1.6k across the 45 of their papers we have counts for
4 papers · 1 filter
Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires
Bryan Lim, Luca Grillotti, Lorenzo Bernasconi +1
Quality-Diversity (QD) algorithms are powerful exploration algorithms that allow robots to discover large repertoires of diverse and high-performing skills. However, QD algorithms…
Unsupervised Behaviour Discovery with Quality-Diversity Optimisation
Luca Grillotti, Antoine Cully
Quality-Diversity algorithms refer to a class of evolutionary algorithms designed to find a collection of diverse and high-performing solutions to a given problem. In robotics, suc…
Policy Manifold Search: Exploring the Manifold Hypothesis for Diversity-based Neuroevolution
Nemanja Rakicevic, Antoine Cully, Petar Kormushev
Neuroevolution is an alternative to gradient-based optimisation that has the potential to avoid local minima and allows parallelisation. The main limiting factor is that usually it…
On the Just-In-Time Discovery of Profit-Generating Transactions in DeFi Protocols
Liyi Zhou, Kaihua Qin, Antoine Cully +2
In this paper, we investigate two methods that allow us to automatically create profitable DeFi trades, one well-suited to arbitrage and the other applicable to more complicated se…