11 citations · 13 across the 13 of their papers we have counts for
6 papers · 1 filter
Learning Diverse Skills for Local Navigation under Multi-constraint Optimality
Jin Cheng, Marin Vlastelica, Pavel Kolev +2
Despite many successful applications of data-driven control in robotics, extracting meaningful diverse behaviors remains a challenge. Typically, task performance needs to be compro…
Real Robot Challenge 2022: Learning Dexterous Manipulation from Offline Data in the Real World
Nico Gürtler, Felix Widmaier, Cansu Sancaktar +21
Experimentation on real robots is demanding in terms of time and costs. For this reason, a large part of the reinforcement learning (RL) community uses simulators to develop and be…
Benchmarking Offline Reinforcement Learning on Real-Robot Hardware
Nico Gürtler, Sebastian Blaes, Pavel Kolev +5
Learning policies from previously recorded data is a promising direction for real-world robotics tasks, as online learning is often infeasible. Dexterous manipulation in particular…
Offline Diversity Maximization Under Imitation Constraints
Marin Vlastelica, Jin Cheng, Georg Martius +1
There has been significant recent progress in the area of unsupervised skill discovery, utilizing various information-theoretic objectives as measures of diversity. Despite these a…
On Imitation in Mean-field Games
Giorgia Ramponi, Pavel Kolev, Olivier Pietquin +3
We explore the problem of imitation learning (IL) in the context of mean-field games (MFGs), where the goal is to imitate the behavior of a population of agents following a Nash eq…
Online Learning under Adversarial Nonlinear Constraints
Pavel Kolev, Georg Martius, Michael Muehlebach
In many applications, learning systems are required to process continuous non-stationary data streams. We study this problem in an online learning framework and propose an algorith…