2k citations · 2.2k across the 27 of their papers we have counts for
9 papers · 1 filter
Deep Model-Based Reinforcement Learning for High-Dimensional Problems, a Survey
Aske Plaat, Walter Kosters, Mike Preuss
Deep reinforcement learning has shown remarkable success in the past few years. Highly complex sequential decision making problems have been solved in tasks such as game playing an…
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…
Warm-Start AlphaZero Self-Play Search Enhancements
Hui Wang, Mike Preuss, Aske Plaat
Recently, AlphaZero has achieved landmark results in deep reinforcement learning, by providing a single self-play architecture that learned three different games at super human lev…
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…
From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI
Sebastian Risi, Mike Preuss
This paper reviews the field of Game AI, which not only deals with creating agents that can play a certain game, but also with areas as diverse as creating game content automatical…