6 papers
Offline Goal-Conditioned Reinforcement Learning with Projective Quasimetric Planning
Anthony Kobanda, Waris Radji, Mathieu Petitbois +2
Offline Goal-Conditioned Reinforcement Learning seeks to train agents to reach specified goals from previously collected trajectories. Scaling that promises to long-horizon tasks r…
A Continual Offline Reinforcement Learning Benchmark for Navigation Tasks
Anthony Kobanda, Odalric-Ambrym Maillard, Rémy Portelas
Autonomous agents operating in domains such as robotics or video game simulations must adapt to changing tasks without forgetting about the previous ones. This process called Conti…
Offline Learning of Controllable Diverse Behaviors
Mathieu Petitbois, Rémy Portelas, Sylvain Lamprier +1
Imitation Learning (IL) techniques aim to replicate human behaviors in specific tasks. While IL has gained prominence due to its effectiveness and efficiency, traditional methods o…
Hierarchical Subspaces of Policies for Continual Offline Reinforcement Learning
Anthony Kobanda, Rémy Portelas, Odalric-Ambrym Maillard +1
We consider a Continual Reinforcement Learning setup, where a learning agent must continuously adapt to new tasks while retaining previously acquired skill sets, with a focus on th…
Navigation with QPHIL: Quantizing Planner for Hierarchical Implicit Q-Learning
Alexi Canesse, Mathieu Petitbois, Ludovic Denoyer +2
Offline Reinforcement Learning (RL) has emerged as a powerful alternative to imitation learning for behavior modeling in various domains, particularly in complex navigation tasks.…
Efficient Active Imitation Learning with Random Network Distillation
Emilien Biré, Anthony Kobanda, Ludovic Denoyer +1
Developing agents for complex and underspecified tasks, where no clear objective exists, remains challenging but offers many opportunities. This is especially true in video games,…