Search Results for author: Maxim Peter

Found 4 papers, 1 papers with code

Graph augmented Deep Reinforcement Learning in the GameRLand3D environment

no code implementations22 Dec 2021 Edward Beeching, Maxim Peter, Philippe Marcotte, Jilles Debangoye, Olivier Simonin, Joshua Romoff, Christian Wolf

We address planning and navigation in challenging 3D video games featuring maps with disconnected regions reachable by agents using special actions.

reinforcement-learning Reinforcement Learning (RL)

Deep Reinforcement Learning for Navigation in AAA Video Games

no code implementations9 Nov 2020 Eloi Alonso, Maxim Peter, David Goumard, Joshua Romoff

We test our approach on complex 3D environments in the Unity game engine that are notably an order of magnitude larger than maps typically used in the Deep RL literature.

Navigate reinforcement-learning +2

Discrete and Continuous Action Representation for Practical RL in Video Games

1 code implementation23 Dec 2019 Olivier Delalleau, Maxim Peter, Eloi Alonso, Adrien Logut

While most current research in Reinforcement Learning (RL) focuses on improving the performance of the algorithms in controlled environments, the use of RL under constraints like those met in the video game industry is rarely studied.

Control with Prametrised Actions Reinforcement Learning (RL)

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