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A survey of human-in-the-loop for machine learning
Abstract Machine learning has become the state-of-the-art technique for many tasks
including computer vision, natural language processing, speech processing tasks, etc …
including computer vision, natural language processing, speech processing tasks, etc …
Human-in-the-loop reinforcement learning: A survey and position on requirements, challenges, and opportunities
Artificial intelligence (AI) and especially reinforcement learning (RL) have the potential to
enable agents to learn and perform tasks autonomously with superhuman performance …
enable agents to learn and perform tasks autonomously with superhuman performance …
What matters in learning from offline human demonstrations for robot manipulation
Imitating human demonstrations is a promising approach to endow robots with various
manipulation capabilities. While recent advances have been made in imitation learning and …
manipulation capabilities. While recent advances have been made in imitation learning and …
Interactive imitation learning in robotics: A survey
Interactive Imitation Learning in Robotics: A Survey Page 1 Interactive Imitation Learning in
Robotics: A Survey Page 2 Other titles in Foundations and Trends® in Robotics A Survey on …
Robotics: A Survey Page 2 Other titles in Foundations and Trends® in Robotics A Survey on …
Model-free reinforcement learning from expert demonstrations: a survey
Reinforcement learning from expert demonstrations (RLED) is the intersection of imitation
learning with reinforcement learning that seeks to take advantage of these two learning …
learning with reinforcement learning that seeks to take advantage of these two learning …
Wearable EEG electronics for a Brain–AI Closed-Loop System to enhance autonomous machine decision-making
Human nonverbal communication tools are very ambiguous and difficult to transfer to
machines or artificial intelligence (AI). If the AI understands the mental state behind a user's …
machines or artificial intelligence (AI). If the AI understands the mental state behind a user's …
Transic: Sim-to-real policy transfer by learning from online correction
Learning in simulation and transferring the learned policy to the real world has the potential
to enable generalist robots. The key challenge of this approach is to address simulation-to …
to enable generalist robots. The key challenge of this approach is to address simulation-to …
Robot learning on the job: Human-in-the-loop autonomy and learning during deployment
With the rapid growth of computing powers and recent advances in deep learning, we have
witnessed impressive demonstrations of novel robot capabilities in research settings …
witnessed impressive demonstrations of novel robot capabilities in research settings …
A survey on explainable reinforcement learning: Concepts, algorithms, challenges
Reinforcement Learning (RL) is a popular machine learning paradigm where intelligent
agents interact with the environment to fulfill a long-term goal. Driven by the resurgence of …
agents interact with the environment to fulfill a long-term goal. Driven by the resurgence of …
Human-in-the-loop imitation learning using remote teleoperation
Imitation Learning is a promising paradigm for learning complex robot manipulation skills by
reproducing behavior from human demonstrations. However, manipulation tasks often …
reproducing behavior from human demonstrations. However, manipulation tasks often …