963 citations · 3.1k across the 34 of their papers we have counts for
4 papers · 1 filter
An Online Data-Driven Emergency-Response Method for Autonomous Agents in Unforeseen Situations
Glenn Maguire, Nicholas Ketz, Praveen Pilly +1
Reinforcement learning agents perform well when presented with inputs within the distribution of those encountered during training. However, they are unable to respond effectively…
Learning a Behavioral Repertoire from Demonstrations
Niels Justesen, Miguel Gonzalez Duque, Daniel Cabarcas Jaramillo +2
Imitation Learning (IL) is a machine learning approach to learn a policy from a dataset of demonstrations. IL can be useful to kick-start learning before applying reinforcement lea…
Multi-objective Model-based Policy Search for Data-efficient Learning with Sparse Rewards
Rituraj Kaushik, Konstantinos Chatzilygeroudis, Jean-Baptiste Mouret
The most data-efficient algorithms for reinforcement learning in robotics are model-based policy search algorithms, which alternate between learning a dynamical model of the robot…
Limbo: A Fast and Flexible Library for Bayesian Optimization
Antoine Cully, Konstantinos Chatzilygeroudis, Federico Allocati +1
Limbo is an open-source C++11 library for Bayesian optimization which is designed to be both highly flexible and very fast. It can be used to optimize functions for which the gradi…