15 citations · 28 across the 3 of their papers we have counts for
3 papers
cs.LG2021★ 15 cited
SKID RAW: Skill Discovery from Raw Trajectories
Daniel Tanneberg, Kai Ploeger, Elmar Rueckert +1
Integrating robots in complex everyday environments requires a multitude of problems to be solved. One crucial feature among those is to equip robots with a mechanism for teaching…
cs.RO2020★ 13 cited
High Acceleration Reinforcement Learning for Real-World Juggling with Binary Rewards
Kai Ploeger, Michael Lutter, Jan Peters
Robots that can learn in the physical world will be important to en-able robots to escape their stiff and pre-programmed movements. For dynamic high-acceleration tasks, such as jug…
cs.LG2019
Learning walk and trot from the same objective using different types of exploration
Zinan Liu, Kai Ploeger, Svenja Stark +2
In quadruped gait learning, policy search methods that scale high dimensional continuous action spaces are commonly used. In most approaches, it is necessary to introduce prior kno…