This report documents the program and the outcomes of Dagstuhl Seminar 11131 ``Exploration and Curiosity in Robot Learning and Inference\u27\u27. This seminar was concerned with answering the question: how should a robot choose its actions and experiences so as to maximise the effectiveness of its learning?}. The seminar brought together workers from three fields: machine learning, robotics and computational neuroscience. The seminar gave an overview of active research, and identified open research problems. In particular the seminar identified the difficulties in moving from theoretically well grounded notions of curiosity to practical robot implementations
Creating autonomous robots that can learn to act in unpredictable environments has been a long-stand...
High performance robot arms are faster, more accurate, and stronger than humans. Yet many manipulat...
This article posits the idea of robot learning as a new subfield. The results of the Robolearn-96 Wo...
This report documents the program and the outcomes of Dagstuhl Seminar 11131 “Exploration and Curios...
This report documents the programme and the outcomes of Dagstuhl Seminar 14081 "Robots Learning from...
From 16.08. to 21.08.2009, the Dagstuhl Seminar 09341 ``Cognition, Control and Learning for Robot Ma...
The work presented in this dissertation investigates techniques for robot Learning from Demonstratio...
From 19.06.06 to 23.06.06, the Dagstuhl Seminar 06251 ``Multi-Robot Systems: Perception, Behaviors, ...
From 03.10.10 to 08.10.10,the Dagstuhl Seminar 10401 ``Learning, Planning and Sharing Robot Knowledg...
This dissertation presents an approach to robot programming by demonstration based on two key concep...
Robots must successfully execute tasks in the presence of uncertainty. The main sources of uncertain...
Robot Learning is intended for one term advanced Machine Learning courses taken by students from dif...
Building robots that are able to efficiently operate in the real world is a formidable challenge. Fu...
Curiosity is a core drive for learning in humans which is increasingly being looked at in developing...
In this paper we outline some ideas as to how robot learning experiments might best be designed, bas...
Creating autonomous robots that can learn to act in unpredictable environments has been a long-stand...
High performance robot arms are faster, more accurate, and stronger than humans. Yet many manipulat...
This article posits the idea of robot learning as a new subfield. The results of the Robolearn-96 Wo...
This report documents the program and the outcomes of Dagstuhl Seminar 11131 “Exploration and Curios...
This report documents the programme and the outcomes of Dagstuhl Seminar 14081 "Robots Learning from...
From 16.08. to 21.08.2009, the Dagstuhl Seminar 09341 ``Cognition, Control and Learning for Robot Ma...
The work presented in this dissertation investigates techniques for robot Learning from Demonstratio...
From 19.06.06 to 23.06.06, the Dagstuhl Seminar 06251 ``Multi-Robot Systems: Perception, Behaviors, ...
From 03.10.10 to 08.10.10,the Dagstuhl Seminar 10401 ``Learning, Planning and Sharing Robot Knowledg...
This dissertation presents an approach to robot programming by demonstration based on two key concep...
Robots must successfully execute tasks in the presence of uncertainty. The main sources of uncertain...
Robot Learning is intended for one term advanced Machine Learning courses taken by students from dif...
Building robots that are able to efficiently operate in the real world is a formidable challenge. Fu...
Curiosity is a core drive for learning in humans which is increasingly being looked at in developing...
In this paper we outline some ideas as to how robot learning experiments might best be designed, bas...
Creating autonomous robots that can learn to act in unpredictable environments has been a long-stand...
High performance robot arms are faster, more accurate, and stronger than humans. Yet many manipulat...
This article posits the idea of robot learning as a new subfield. The results of the Robolearn-96 Wo...