@article{Tanneberg2021,

title = {SKID RAW: Skill Discovery from Raw Trajectories},

author = {Daniel Tanneberg and Kai Ploeger and Elmar Rueckert and Jan Peters },

url = {https://cps.unileoben.ac.at/wp/RAL2021Tanneberg.pdf, Article File},

issn = {2377-3766},

year  = {2021},

date = {2021-03-10},

journal = {IEEE Robotics and Automation Letters (RA-L)},

pages = {1--8},

note = {© 20XX IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.},

keywords = {Manipulation, movement primitives, Probabilistic Inference},

pubstate = {published},

tppubtype = {article}

}

@article{Cansev2021,

title = {Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience},

author = {Mehmet Ege Cansev and Honghu Xue and Nils Rottmann and Adna Bliek and Luke E. Miller and Elmar Rueckert and Philipp Beckerle},

url = {https://cps.unileoben.ac.at/wp/AIS2021Cansev.pdf, Article File},

doi = {10.1002/aisy.202000247},

year  = {2021},

date = {2021-03-10},

journal = {Advanced Intelligent Systems},

pages = {1--28},

keywords = {human motor control, intrinsic motivation, movement primitives, Probabilistic Inference, Reinforcement Learning, spiking},

pubstate = {published},

tppubtype = {article}

}

@article{Tanneberg2019,

title = {Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks},

author = {Daniel Tanneberg and Jan Peters and Elmar Rueckert},

url = {https://cps.unileoben.ac.at/wp/NeuralNetworks2018Tanneberg.pdf, Article File},

doi = {10.1016/j.neunet.2018.10.005},

isbn = {0893-6080},

year  = {2019},

date = {2019-01-01},

journal = {Neural Networks - Elsevier},

volume = {109},

pages = {67-80},

note = {Impact Factor of 7.197 (2017)},

keywords = {neural network, Probabilistic Inference, RNN, spiking},

pubstate = {published},

tppubtype = {article}

}

@article{Sosic2018,

title = {Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling},

author = {Adrian Sosic and Abdelhak M. Zoubir and Elmar Rueckert and Jan Peters and

Heinz Koeppl},

url = {https://cps.unileoben.ac.at/wp/JMLR2018Sosic.pdf, Preprint Article File},

year  = {2018},

date = {2018-10-08},

journal = {Journal of Machine Learning Research (JMLR)},

volume = {19},

number = {69},

pages = {1-45},

keywords = {movement primitives, Probabilistic Inference, Simulation},

pubstate = {published},

tppubtype = {article}

}

@article{Rueckert2013,

title = { Learned graphical models for probabilistic planning provide a new class of movement primitives},

author = {Elmar Rueckert and Gerhard Neumann and Marc Toussaint and Wolfgang Maass},

url = {https://cps.unileoben.ac.at/wp/Frontiers2013aRueckert.pdf, Article File},

doi = {10.3389/fncom.2012.00097},

year  = {2013},

date = {2013-01-02},

journal = {Frontiers in Computational Neuroscience},

volume = {6},

number = {97},

keywords = {graphical models, movement primitives, Probabilistic Inference},

pubstate = {published},

tppubtype = {article}

}

@article{Rueckert2012,

title = {Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation},

author = {Elmar Rueckert and Gerhard Neumann},

url = {https://cps.unileoben.ac.at/wp/ArtificialLife2012Rueckert.pdf, Article File},

doi = {10.1162/ARTL_a_00085},

year  = {2012},

date = {2012-11-27},

journal = {Artificial Life},

volume = {19},

number = {1},

keywords = {morphological compuation, Probabilistic Inference, SOC},

pubstate = {published},

tppubtype = {article}

}

@article{Tanneberg2021,

title = {SKID RAW: Skill Discovery from Raw Trajectories},

author = {Daniel Tanneberg and Kai Ploeger and Elmar Rueckert and Jan Peters },

url = {https://cps.unileoben.ac.at/wp/RAL2021Tanneberg.pdf, Article File},

issn = {2377-3766},

year  = {2021},

date = {2021-03-10},

journal = {IEEE Robotics and Automation Letters (RA-L)},

pages = {1--8},

note = {© 20XX IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cansev2021,

title = {Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience},

author = {Mehmet Ege Cansev and Honghu Xue and Nils Rottmann and Adna Bliek and Luke E. Miller and Elmar Rueckert and Philipp Beckerle},

url = {https://cps.unileoben.ac.at/wp/AIS2021Cansev.pdf, Article File},

doi = {10.1002/aisy.202000247},

year  = {2021},

date = {2021-03-10},

journal = {Advanced Intelligent Systems},

pages = {1--28},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Tanneberg2019,

title = {Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks},

author = {Daniel Tanneberg and Jan Peters and Elmar Rueckert},

url = {https://cps.unileoben.ac.at/wp/NeuralNetworks2018Tanneberg.pdf, Article File},

doi = {10.1016/j.neunet.2018.10.005},

isbn = {0893-6080},

year  = {2019},

date = {2019-01-01},

journal = {Neural Networks - Elsevier},

volume = {109},

pages = {67-80},

note = {Impact Factor of 7.197 (2017)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Sosic2018,

title = {Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling},

author = {Adrian Sosic and Abdelhak M. Zoubir and Elmar Rueckert and Jan Peters and

Heinz Koeppl},

url = {https://cps.unileoben.ac.at/wp/JMLR2018Sosic.pdf, Preprint Article File},

year  = {2018},

date = {2018-10-08},

journal = {Journal of Machine Learning Research (JMLR)},

volume = {19},

number = {69},

pages = {1-45},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rueckert2013,

title = { Learned graphical models for probabilistic planning provide a new class of movement primitives},

author = {Elmar Rueckert and Gerhard Neumann and Marc Toussaint and Wolfgang Maass},

url = {https://cps.unileoben.ac.at/wp/Frontiers2013aRueckert.pdf, Article File},

doi = {10.3389/fncom.2012.00097},

year  = {2013},

date = {2013-01-02},

journal = {Frontiers in Computational Neuroscience},

volume = {6},

number = {97},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rueckert2012,

title = {Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation},

author = {Elmar Rueckert and Gerhard Neumann},

url = {https://cps.unileoben.ac.at/wp/ArtificialLife2012Rueckert.pdf, Article File},

doi = {10.1162/ARTL_a_00085},

year  = {2012},

date = {2012-11-27},

journal = {Artificial Life},

volume = {19},

number = {1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}