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Turn-taking, Children, and the Unpredictability of Fun

Turn-taking, Children, and the Unpredictability of Fun

by Sarah Frigg | Sep 1, 2016 | Machine Learning

Turn-taking, Children, and the Unpredictability of Fun   When the goal is entertainment, designing language-based interactions between characters and small groups of young children is a balancing act. September 1, 2016AI Magazine 2016   Authors Jill Fain...
Imitating Human Movement with Teleoperated Robotic Head

Imitating Human Movement with Teleoperated Robotic Head

by Sarah Frigg | Aug 26, 2016 | Robotics

Imitating Human Movement with Teleoperated Robotic Head   We develop a controller for realizing smooth and accurate motion of a robotic head with application to a teleoperation system for the Furhat robot head. August 26, 2016International Symposium on Robot and Human...
Maintaining Awareness of the Focus of Attention of a Conversation: A Robot-Centric Reinforcement Learning Approach

Maintaining Awareness of the Focus of Attention of a Conversation: A Robot-Centric Reinforcement Learning Approach

by Sarah Frigg | Aug 26, 2016 | Uncategorized

Maintaining Awareness of the Focus of Attention of a Conversation: A Robot-Centric Reinforcement Learning Approach    We explore online reinforcement learning techniques to find good policies to control the orientation of a mobile robot during social group...
Study of Children’s Hugging for Interactive Robot Design

Study of Children’s Hugging for Interactive Robot Design

by Sarah Frigg | Aug 26, 2016 | Robotics

Study of Children’s Hugging for Interactive Robot Design   We have developed a toy sized humanoid robot with soft air-filled modules on its links which sense contact and protect the robot and any interacting humans from damaging collisions. August 26,...
Multiplicative Representation for Unsupervised Semantic Role Induction

Multiplicative Representation for Unsupervised Semantic Role Induction

by Sarah Frigg | Aug 7, 2016 | Machine Learning

Multiplicative Representation for Unsupervised Semantic Role Induction   We propose a neural model to learn argument embeddings from the context by explicitly incorporating dependency relations as multiplicative factors. August 7, 2016The Annual Meeting of the...
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