Inferring human intent and predicting human action in human–robot collaboration
Researchers in human–robot collaboration have extensively studied methods for inferring
human intentions and predicting their actions, as this is an important precursor for robots to …
human intentions and predicting their actions, as this is an important precursor for robots to …
A survey of progress on cooperative multi-agent reinforcement learning in open environment
When are two lists better than one?: Benefits and harms in joint decision-making
Historically, much of machine learning research has focused on the performance of the
algorithm alone, but recently more attention has been focused on optimizing joint human …
algorithm alone, but recently more attention has been focused on optimizing joint human …
A review of communicating robot learning during human-robot interaction
For robots to seamlessly interact with humans, we first need to make sure that humans and
robots understand one another. Diverse algorithms have been developed to enable robots …
robots understand one another. Diverse algorithms have been developed to enable robots …
A survey of communicating robot learning during human-robot interaction
For robots to seamlessly interact with humans, we first need to make sure that humans and
robots understand one another. Diverse algorithms have been developed to enable robots …
robots understand one another. Diverse algorithms have been developed to enable robots …
AI-Assisted Decision Making with Human Learning
AI systems increasingly support human decision-making. In many cases, despite the
algorithm's superior performance, the final decision remains in human hands. For example …
algorithm's superior performance, the final decision remains in human hands. For example …
StROL: Stabilized and robust online learning from humans
Robots often need to learn the human's reward function online, during the current
interaction. This real-time learning requires fast but approximate learning rules: when the …
interaction. This real-time learning requires fast but approximate learning rules: when the …
Simultaneously learning intentions and preferences during physical human-robot cooperation
The advent of collaborative robots allows humans and robots to cooperate in a direct and
physical way. While this leads to amazing new opportunities to create novel robotics …
physical way. While this leads to amazing new opportunities to create novel robotics …
Towards proactive safe human-robot collaborations via data-efficient conditional behavior prediction
We focus on the problem of how we can enable a robot to collaborate seamlessly with a
human partner, specifically in scenarios where preexisting data is sparse. Much prior work in …
human partner, specifically in scenarios where preexisting data is sparse. Much prior work in …