Action Spaces in Deep Reinforcement Learning to Mimic Human Input Devices. - Marco Pleines; Frank Zimmer; Vincent-Pierre Berges (CoG, 2019)

Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning. - Marco Pleines; Jenia Jitsev; Mike Preuss; Frank Zimmer (CoG, 2020)

On the Verge of Solving Rocket League using Deep Reinforcement Learning and Sim-to-sim Transfer. - Marco Pleines; Konstantin Ramthun; Yannik Wegener; Hendrik Meyer; Matthias Pallasch; Sebastian Prior; Jannik Drögemüller; Leon Büttinghaus; Thilo Röthemeyer; Alexander Kaschwig; Oliver Chmurzynski; Frederik Rohkrähmer; et al. (CoG, 2022)

Improving Bidding and Playing Strategies in the Trick-Taking game Wizard using Deep Q-Networks. - Jonas Schumacher; Marco Pleines (CoG, 2022)

Generalization, Mayhems and Limits in Recurrent Proximal Policy Optimization. - Marco Pleines; Matthias Pallasch; Frank Zimmer; Mike Preuss (CoRR, 2022)

Memory Gym: Partially Observable Challenges to Memory-Based Agents. - Marco Pleines; Matthias Pallasch; Frank Zimmer; Mike Preuss (ICLR, 2023)

Memory Gym: Partially Observable Challenges to Memory-Based Agents in Endless Episodes. - Marco Pleines; Matthias Pallasch; Frank Zimmer; Mike Preuss (CoRR, 2023)

Memory-based deep reinforcement learning in endless imperfect information games. - Marco Pleines (2023)

Pokémon Red via Reinforcement Learning. - Marco Pleines; Daniel Addis; David Rubinstein; Frank Zimmer; Mike Preuss; Peter Whidden (CoG, 2025)

Playing Pokémon Red via Deep Reinforcement Learning. - Marco Pleines; Daniel Addis; David Rubinstein; Frank Zimmer; Mike Preuss; Peter Whidden (CoRR, 2025)