Using Gaussian Mixture models to detect figurative language in context
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Mimetic Communication Model with Compliant Physical Contact in Human-Humanoid Interaction
International Journal of Robotics Research
On internal knowledge representation for programming mobile robots by demonstration
ICSR'10 Proceedings of the Second international conference on Social robotics
On-line regression algorithms for learning mechanical models of robots: A survey
Robotics and Autonomous Systems
Interactive imitation learning of object movement skills
Autonomous Robots
Situated learning of visual robot behaviors
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part I
Imitation learning in relational domains: a functional-gradient boosting approach
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
A robot learning from demonstration framework to perform force-based manipulation tasks
Intelligent Service Robotics
MotionMA: motion modelling and analysis by demonstration
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Learning to select and generalize striking movements in robot table tennis
International Journal of Robotics Research
A syntactic approach to robot imitation learning using probabilistic activity grammars
Robotics and Autonomous Systems
Reasons for singularity in robot teleoperation
Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction
Socially guided intrinsic motivation for robot learning of motor skills
Autonomous Robots
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Also referred to as learning by imitation, tutelage, or apprenticeship learning, Programming by Demonstration (PbD) develops methods by which new skills can be transmitted to a robot. This book examines methods by which robots learn new skills through human guidance. Taking a practical perspective, it covers a broad range of applications, including service robots. The text addresses the challenges involved in investigating methods by which PbD is used to provide robots with a generic and adaptive model of control. Drawing on findings from robot control, human-robot interaction, applied machine learning, artificial intelligence, and developmental and cognitive psychology, the book contains a large set of didactic and illustrative examples. Practical and comprehensive machine learning source codes are available on the books companion website: http://www.programming-by-demonstration.org