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Found 4 papers, 1 papers with code
Single-Task Continual Offline Reinforcement Learning
In this paper, we study the continual learning problem of single-task offline reinforcement learning.
RSG: Fast Learning Adaptive Skills for Quadruped Robots by Skill Graph
Developing robotic intelligent systems that can adapt quickly to unseen wild situations is one of the critical challenges in pursuing autonomous robotics.
Beyond OOD State Actions: Supported Cross-Domain Offline Reinforcement Learning
Offline reinforcement learning (RL) aims to learn a policy using only pre-collected and fixed data.
OER: Offline Experience Replay for Continual Offline Reinforcement Learning
In this paper, we formulate a new setting, continual offline reinforcement learning (CORL), where an agent learns a sequence of offline reinforcement learning tasks and pursues good performance on all learned tasks with a small replay buffer without exploring any of the environments of all the sequential tasks.
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