1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Putting the Iterative Training of Decision Trees to the Test on a Real-World Robotic Task
Raphael C. Engelhardt, Marcel J. Meinen, Moritz Lange +2
In previous research, we developed methods to train decision trees (DT) as agents for reinforcement learning tasks, based on deep reinforcement learning (DRL) networks. The samples…
cs.LG2024
Interpretable Brain-Inspired Representations Improve RL Performance on Visual Navigation Tasks
Moritz Lange, Raphael C. Engelhardt, Wolfgang Konen +1
Visual navigation requires a whole range of capabilities. A crucial one of these is the ability of an agent to determine its own location and heading in an environment. Prior works…
cs.LG2023★ 1 cited
Towards Learning Rubik's Cube with N-tuple-based Reinforcement Learning
Wolfgang Konen
This work describes in detail how to learn and solve the Rubik's cube game (or puzzle) in the General Board Game (GBG) learning and playing framework. We cover the cube sizes 2x2x2…