Learning by Teaching: Designing Teachable Agents to Support Children's Pronunciation Skill Learning

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Leading researchers debate the long-term influence of model-free methods that use large sets of demonstration data to train numerical generative models to control robots. ...

Soft robots, compared to rigid robots, possess inherent advantages, including higher degrees of freedom, compliance, and enhanced safety, which have contributed to their increasing application across various fields. Among these benefits, adaptability is pa ...

As urban populations continue to expand and vehicle density increases, the need for effective traffic monitoring and management becomes increasingly critical. Urban areas face significant challenges such as growing congestion, safety concerns, and parking ...

Robust in-hand manipulation of objects with movable content requires estimation and prediction of the contents' motion with enough anticipation to allow time to compensate for resulting internal torques. The quick estimation of the objects' dynamics can be ...

Robotic fruit harvesting requires dexterity to handle delicate crops and development relying upon field testing possible only during the harvesting season. Here we focus on raspberry crops, and explore how the research methodology of harvesting robots can ...

The process of quantifying and analyzing animal behavior involves translating the naturally occurring descriptive language of their actions into machine-readable code. Yet, codifying behavior analysis is often challenging without deep understanding of anim ...

Autonomous robots have the potential to fundamentally transform conventional farming methods, e.g. by enabling economically viable farming of sloped arable land. However, navigation on slopes in harsh conditions is challenging for robots as they must be pr ...

The imaginary-time evolution of quantum states is integral to various fields, ranging from natural sciences to classical optimization or machine learning. Since simulating quantum imaginary-time evolution generally requires storing an exponentially large w ...

In this paper, we propose a learning algorithm that enables a model to quickly exploit commonalities among related tasks from an unseen task distribution, before quickly adapting to specific tasks from that same distribution. We investigate how learning wi ...

One of the numerous approaches that increases the interaction quality between two people is having a proper understanding of the other person's perspective. In this doctoral thesis, we aim to understand children's perspective taking behavior, create a pers ...

Learning by Teaching: Designing Teachable Agents to Support Children's Pronunciation Skill Learning

Chattez avec Graph Search

“Data will solve robotics and automation: True or false?”: A debate

A Survey on Soft Robot Adaptability: Implementations, Applications, and Prospects [Survey]

Drone-Based Urban Traffic Monitoring and User Behavior Prediction

A Predictive Model for Tactile Force Estimation Using Audio-Tactile Data

Lab2Field transfer of a robotic raspberry harvester enabled by a soft sensorized physical twin

AmadeusGPT: a natural language interface for interactive animal behavioral analysis

Automation in steep terrain agriculture: an optimal controller to prevent tipping and slipping of tethered robots on slopes

Learning the rules of mitochondrial network dynamics using generative models

Stochastic Approximation of Variational Quantum Imaginary Time Evolution

Model-Agnostic Learning to Meta-Learn

Changing Perspective as A Learning Mechanism