58 citations · 83 across the 5 of their papers we have counts for
9 papers
Tackling Morpion Solitaire with AlphaZero-likeRanked Reward Reinforcement Learning
Hui Wang, Mike Preuss, Michael Emmerich +1
Morpion Solitaire is a popular single player game, performed with paper and pencil. Due to its large state space (on the order of the game of Go) traditional search algorithms, suc…
Versatile Black-Box Optimization
Jialin Liu, Antoine Moreau, Mike Preuss +4
Choosing automatically the right algorithm using problem descriptors is a classical component of combinatorial optimization. It is also a good tool for making evolutionary algorith…
Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning
Marco Pleines, Jenia Jitsev, Mike Preuss +1
The Obstacle Tower Challenge is the task to master a procedurally generated chain of levels that subsequently get harder to complete. Whereas the most top performing entries of las…
A New Challenge: Approaching Tetris Link with AI
Matthias Muller-Brockhausen, Mike Preuss, Aske Plaat
Decades of research have been invested in making computer programs for playing games such as Chess and Go. This paper focuses on a new game, Tetris Link, a board game that is still…
FakeYou! -- A Gamified Approach for Building and Evaluating Resilience Against Fake News
Lena Clever, Dennis Assenmacher, Kilian Müller +4
Nowadays fake news are heavily discussed in public and political debates. Even though the phenomenon of intended false information is rather old, misinformation reaches a new level…
Analysis of Hyper-Parameters for Small Games: Iterations or Epochs in Self-Play?
Hui Wang, Michael Emmerich, Mike Preuss +1
The landmark achievements of AlphaGo Zero have created great research interest into self-play in reinforcement learning. In self-play, Monte Carlo Tree Search is used to train a de…