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cs.LG2024
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…
cs.LG2024
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.…
cs.LG2024
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,…