Proximal State Nudging (PSN) jointly optimizes skill development and task performance in shared autonomy, outperforming baselines in LunarLander simulation and yielding up to 7x larger unassisted skill gains with 50% fewer collisions in human CARLA driving studies.
Deep reinforcement learning with double q-learning,
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
Hybrid agent with variational quantum circuits for feature extraction in hierarchical RL outperforms classical baselines with 66% parameter savings, but quantum value estimation degrades results.
citing papers explorer
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Proximal State Nudging: Reducing Skill Atrophy from AI Assistance
Proximal State Nudging (PSN) jointly optimizes skill development and task performance in shared autonomy, outperforming baselines in LunarLander simulation and yielding up to 7x larger unassisted skill gains with 50% fewer collisions in human CARLA driving studies.
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Quantum Hierarchical Reinforcement Learning via Variational Quantum Circuits
Hybrid agent with variational quantum circuits for feature extraction in hierarchical RL outperforms classical baselines with 66% parameter savings, but quantum value estimation degrades results.