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Robots can learn preferences from human demonstrations, but their success depends on how informative these demonstrations are. Being informative is unfortunately very challenging, because during teaching, people typically get no…

Robotics · Computer Science 2019-11-07 Sandy H. Huang , Isabella Huang , Ravi Pandya , Anca D. Dragan

Discrepancies between an agent's actual knowledge and what a person thinks the agent knows can hinder interactions. If an agent could detect such discrepancies, it could provide feedback to account for them and improve current and future…

Human-Computer Interaction · Computer Science 2026-05-14 Patrick Callaghan , Reid Simmons , Henny Admoni

In social robotics, robots needs to be able to be understood by humans. Especially in collaborative tasks where they have to share mutual knowledge. For instance, in an educative scenario, learners share their knowledge and they must adapt…

Robotics · Computer Science 2016-02-24 Alexis Jacq , Wafa Johal , Pierre Dillenbourg , Ana Paiva

When cooperating with a human, a robot should not only care about its environment and task but also develop an understanding of the partner's reasoning. To support its human partner in complex tasks, the robot can share information that it…

Robotics · Computer Science 2021-09-06 Moritz C. Buehler , Jürgen Adamy , Thomas H. Weisswange

Assistive robots have the potential to help people perform everyday tasks. However, these robots first need to learn what it is their user wants them to do. Teaching assistive robots is hard for inexperienced users, elderly users, and users…

Robotics · Computer Science 2021-04-06 Ananth Jonnavittula , Dylan P. Losey

As AI systems increasingly take on instructional roles - providing feedback, guiding practice, evaluating work - a fundamental question emerges: does it matter to learners who they believe is on the other side? We investigated this using a…

Human-Computer Interaction · Computer Science 2026-04-06 Caitlin Morris , Pattie Maes

Reward learning algorithms utilize human feedback to infer a reward function, which is then used to train an AI system. This human feedback is often a preference comparison, in which the human teacher compares several samples of AI behavior…

Machine Learning · Computer Science 2023-03-03 Peter Barnett , Rachel Freedman , Justin Svegliato , Stuart Russell

The mental models that humans form of other agents---encapsulating human beliefs about agent goals, intentions, capabilities, and more---create an underlying basis for interaction. These mental models have the potential to affect both the…

Robotics · Computer Science 2020-01-07 Connor Brooks , Daniel Szafir

Building machines capable of efficiently collaborating with humans has been a longstanding goal in artificial intelligence. Especially in the presence of uncertainties, optimal cooperation often requires that humans and artificial agents…

Machine Learning · Computer Science 2024-01-10 Oskar Keurulainen , Gokhan Alcan , Ville Kyrki

Human-in-the-loop learning is gaining popularity, particularly in the field of robotics, because it leverages human knowledge about real-world tasks to facilitate agent learning. When people instruct robots, they naturally adapt their…

Robotics · Computer Science 2024-09-17 Jindan Huang , Isaac Sheidlower , Reuben M. Aronson , Elaine Schaertl Short

The overarching goal of this work is to efficiently enable end-users to correctly anticipate a robot's behavior in novel situations. Since a robot's behavior is often a direct result of its underlying objective function, our insight is that…

Robotics · Computer Science 2018-10-19 Sandy H. Huang , David Held , Pieter Abbeel , Anca D. Dragan

It is incredibly easy for a system designer to misspecify the objective for an autonomous system ("robot''), thus motivating the desire to have the robot learn the objective from human behavior instead. Recent work has suggested that people…

Artificial Intelligence · Computer Science 2019-07-02 Smitha Milli , Anca D. Dragan

Theory of Mind is an essential ability of humans to infer the mental states of others. Here we provide a coherent summary of the potential, current progress, and problems of deep learning approaches to Theory of Mind. We highlight that many…

Machine Learning · Computer Science 2023-02-14 Jaan Aru , Aqeel Labash , Oriol Corcoll , Raul Vicente

Successful teaching entails a complex interaction between a teacher and a learner. The teacher must select and convey information based on what they think the learner perceives and believes. Teaching always involves misaligned beliefs, but…

Computation and Language · Computer Science 2020-12-17 Theodore R. Sumers , Mark K. Ho , Thomas L. Griffiths

When learners receive feedback, what they believe about its source may shape how they engage with it. As AI is used alongside human instructors, understanding these attribution effects is essential for designing effective hybrid AI-human…

Human-Computer Interaction · Computer Science 2026-02-13 Caitlin Morris , Pattie Maes

If spreadsheets are not erroneous then who, or what, is? Research has found that end-users are. If end-users are erroneous then why are they? Research has found that responsibility lies with human beings' fast and slow thinking modes and…

Computers and Society · Computer Science 2017-04-06 Mária Csernoch , Piroska Biró

Trust is a critical issue in Human Robot Interactions as it is the core of human desire to accept and use a non human agent. Theory of Mind has been defined as the ability to understand the beliefs and intentions of others that may differ…

Robotics · Computer Science 2021-01-27 Wenxuan Mou , Martina Ruocco , Debora Zanatto , Angelo Cangelosi

The kind of help a student receives during a task has been shown to play a significant role in their learning process. We designed an interaction scenario with a robotic tutor, in real-life settings based on an inquiry-based learning task.…

Human-Computer Interaction · Computer Science 2018-06-21 Maria Blancas-Muñoz , Vasiliki Vouloutsi , Riccardo Zucca , Anna Mura , Paul F. M. J. Verschure

Theory of Mind (ToM) is a fundamental cognitive architecture that endows humans with the ability to attribute mental states to others. Humans infer the desires, beliefs, and intentions of others by observing their behavior and, in turn,…

Robotics · Computer Science 2023-11-09 Chuang Yu , Baris Serhan , Angelo Cangelosi

The ability to model the mental states of others is crucial to human social intelligence, and can offer similar benefits to artificial agents with respect to the social dynamics induced in multi-agent settings. We present a method of…

Machine Learning · Computer Science 2023-07-20 Ini Oguntola , Joseph Campbell , Simon Stepputtis , Katia Sycara
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