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cs.LG2023★ 1 cited
Refining Diffusion Planner for Reliable Behavior Synthesis by Automatic Detection of Infeasible Plans
Kyowoon Lee, Seongun Kim, Jaesik Choi
Diffusion-based planning has shown promising results in long-horizon, sparse-reward tasks by training trajectory diffusion models and conditioning the sampled trajectories using au…
cs.LG2023★ 1 cited
Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills
Seongun Kim, Kyowoon Lee, Jaesik Choi
Mutual information-based reinforcement learning (RL) has been proposed as a promising framework for retrieving complex skills autonomously without a task-oriented reward function t…
cs.RO2023
Adaptive and Explainable Deployment of Navigation Skills via Hierarchical Deep Reinforcement Learning
Kyowoon Lee, Seongun Kim, Jaesik Choi
For robotic vehicles to navigate robustly and safely in unseen environments, it is crucial to decide the most suitable navigation policy. However, most existing deep reinforcement…