Titlebook: Social Robotics; 8th International Co Arvin Agah,John-John Cabibihan,Hongsheng He Conference proceedings 2016 Springer International Publis

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Khaoula Youssef,Jaap Ham,Michio Okadation to intellectual thought on Caribbean security in an increasingly fragmented world. It will be of great interest to students of international security studies, human security, global politics, and international relations. .978-3-030-98735-0978-3-030-98733-6

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Adaptive Robot Assisted Therapy Using Interactive Reinforcement Learning,rgue that Interactive Reinforcement Learning methods can be utilized and integrated to the adaptation mechanism, enabling the agent to refine its learned policy in order to cope with different users. We illustrate our framework with a use case in the domain of Robot Assisted Therapy. We present our

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A Framework for Modelling Local Human-Robot Interactions Based on Unsupervised Learning, of Gaussian Mixture Models (GMMs) to model the physical interaction of the robot and the person when the robot is teleoperated or guided by an expert. The learned models are integrated into a sample-based planner, an RRT*, at two levels: as a cost function in order to plan trajectories considering

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Using Games to Learn Games: Game-Theory Representations as a Source for Guided Social Learning,on in general between a human and a robot. The paper explores the means by which a robot could generate the structure of a game. In addition to offering the formal underpinnings necessary for reasoning about strategy, game theory affords a method for representing the interactive structure of a game

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User Evaluation of an Interactive Learning Framework for Single-Arm and Dual-Arm Robots,n interactive learning framework that enables a user to intervene and modify a segment of the robot arm trajectory. The framework uses gesture teleoperation and reinforcement learning to learn new motions. In the current work, we compared the user experience with the proposed framework implemented o

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