2 papers
cs.AI2020
Action Space Shaping in Deep Reinforcement Learning
Anssi Kanervisto, Christian Scheller, Ville Hautamäki
Reinforcement learning (RL) has been successful in training agents in various learning environments, including video-games. However, such work modifies and shrinks the action space…
cs.LG2020
Sample Efficient Reinforcement Learning through Learning from Demonstrations in Minecraft
Christian Scheller, Yanick Schraner, Manfred Vogel
Sample inefficiency of deep reinforcement learning methods is a major obstacle for their use in real-world applications. In this work, we show how human demonstrations can improve…