C4.5: programs for machine learning
C4.5: programs for machine learning
A tennis serve and upswing learning robot based on bi-directional theory
Neural Networks - Special issue on neural control and robotics: biology and technology
Learning procedural knowledge through observation
Proceedings of the 1st international conference on Knowledge capture
Machine Learning
Robot Shaping: An Experiment in Behavior Engineering
Robot Shaping: An Experiment in Behavior Engineering
ML '92 Proceedings of the Ninth International Workshop on Machine Learning
Imitation in animals and artifacts
Learning and interacting in human-robot domains
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Interactive robot task training through dialog and demonstration
Proceedings of the ACM/IEEE international conference on Human-robot interaction
Incremental learning of gestures by imitation in a humanoid robot
Proceedings of the ACM/IEEE international conference on Human-robot interaction
Confidence-based policy learning from demonstration using Gaussian mixture models
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Human-robot interaction: a survey
Foundations and Trends in Human-Computer Interaction
Human to robot demonstrations of routine home tasks: exploring the role of the robot's feedback
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
Teaching robot companions: the role of scaffolding and event structuring
Connection Science - Social Learning in Embodied Agents
Situated messages for asynchronous human-robot interaction
Proceedings of the 4th ACM/IEEE international conference on Human robot interaction
A survey of robot learning from demonstration
Robotics and Autonomous Systems
Interactive policy learning through confidence-based autonomy
Journal of Artificial Intelligence Research
Learning from demonstration using MDP induced metrics
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Teacher feedback to scaffold and refine demonstrated motion primitives on a mobile robot
Robotics and Autonomous Systems
Robotic grasping and manipulation through human visuomotor learning
Robotics and Autonomous Systems
Perceptual-Motor sequence learning via human-robot interaction
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Tactile Guidance for Policy Adaptation
Foundations and Trends in Robotics
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Programming robots to carry out useful tasks is both a complex and non-trivial exercise. A simple and intuitive method to allow humans to train and shape robot behaviour is clearly a key goal in making this task easier. This paper describes an approach to this problem based on studies of social animals where two teaching strategies are applied to allow a human teacher to train a robot by moulding its actions within a carefully scaffolded environment. Within these enviroments sets of competences can be built by building stateslash action memory maps of the robot's interaction within that environment. These memory maps are then polled using a k-nearest neighbour based algorithm to provide a generalised competence. We take a novel approach in building the memory models by allowing the human teacher to construct them in a hierarchical manner. This mechanism allows a human trainer to build and extend an action-selection mechanism into which new skills can be added to the robot's repertoire of existing competencies. These techniques are implemented on physical Khepera miniature robots and validated on a variety of tasks.