59 citations · 69 across the 6 of their papers we have counts for
6 papers
Gymnasium: A Standard Interface for Reinforcement Learning Environments
Mark Towers, Ariel Kwiatkowski, Jordan Terry +13
Reinforcement Learning (RL) is a continuously growing field that has the potential to revolutionize many areas of artificial intelligence. However, despite its promise, RL research…
Reward Function Design for Crowd Simulation via Reinforcement Learning
Ariel Kwiatkowski, Vicky Kalogeiton, Julien Pettré +1
Crowd simulation is important for video-games design, since it enables to populate virtual worlds with autonomous avatars that navigate in a human-like manner. Reinforcement learni…
UGAE: A Novel Approach to Non-exponential Discounting
Ariel Kwiatkowski, Vicky Kalogeiton, Julien Pettré +1
The discounting mechanism in Reinforcement Learning determines the relative importance of future and present rewards. While exponential discounting is widely used in practice, non-…
Understanding reinforcement learned crowds
Ariel Kwiatkowski, Vicky Kalogeiton, Julien Pettré +1
Simulating trajectories of virtual crowds is a commonly encountered task in Computer Graphics. Several recent works have applied Reinforcement Learning methods to animate virtual a…
A Survey on Reinforcement Learning Methods in Character Animation
Ariel Kwiatkowski, Eduardo Alvarado, Vicky Kalogeiton +4
Reinforcement Learning is an area of Machine Learning focused on how agents can be trained to make sequential decisions, and achieve a particular goal within an arbitrary environme…
Behaviour-conditioned policies for cooperative reinforcement learning tasks
Antti Keurulainen, Isak Westerlund, Ariel Kwiatkowski +2
The cooperation among AI systems, and between AI systems and humans is becoming increasingly important. In various real-world tasks, an agent needs to cooperate with unknown partne…