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Items where Division is "20 Department of Computer Science > Intelligent Autonomous Systems" and Year is [pin missing: value2]

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Number of items at this level (without sub-levels): 28.

A

Arenz, Julian Oleg (2021):
Sample-Efficient I-Projections for Robot Learning. (Publisher's Version)
Darmstadt, Technische Universität,
DOI: 10.12921/tuprints-00014271,
[Ph.D. Thesis]

B

Belousov, Boris and Peters, Jan (2019):
Entropic Regularization of Markov Decision Processes.
21, In: Entropy, (7), MDPI, ISSN 1099-4300,
DOI: 10.3390/e21070674,
[Article]

Büchler, Dieter (2019):
Robot Learning for Muscular Systems. (Publisher's Version)
Darmstadt, Technische Universität,
DOI: 10.25534/tuprints-00017210,
[Ph.D. Thesis]

C

Calandra, Roberto (2017):
Bayesian Modeling for Optimization and Control in Robotics.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

D

Daniel, Christian (2016):
Learning Hierarchical Policies from Human Feedback.
Darmstadt, Technische Universität Darmstadt,
[Ph.D. Thesis]

Delfa Victoria, Juan Manuel (2016):
Automated Hierarchical, Forward-Chaining Temporal Planner for Planetary Robots Exploring Unknown Environments.
Darmstadt, Technische Universität Darmstadt,
[Ph.D. Thesis]

Dezfuli, Niloofar (2015):
Novel Interaction Concepts for Event Participation Through Social Television.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

E

Ewerton, Marco and Arenz, Oleg and Maeda, Guilherme and Koert, Dorothea and Kolev, Zlatko and Takahashi, Masaki and Peters, Jan (2019):
Learning Trajectory Distributions for Assisted Teleoperation and Path Planning.
In: Frontiers in Robotics and AI, 6, Frontiers, e-ISSN 2296-9144,
DOI: 10.25534/tuprints-00009657,
[Article]

F

Fernandes Veiga, Filipe (2018):
Towards Dexterous In-Hand Manipulation through Tactile Sensing.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

G

Gebhardt, Gregor H.W. (2019):
Using Mean Embeddings for State Estimation and Reinforcement Learning.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

Gomez Gonzalez, Sebastian (2020):
Real Time Probabilistic Models for Robot Trajectories.
Darmstadt, Technische Universität Darmstadt,
DOI: 10.25534/tuprints-00011492,
[Ph.D. Thesis]

K

Kober, Jens (2012):
Learning Motor Skills: From Algorithms to Robot Experiments.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

Koc, Okan (2018):
Optimal Trajectory Generation and Learning Control for Robot Table Tennis.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

Koert, Dorothea (2020):
Interactive Machine Learning for Assistive Robots. (Publisher's Version)
Darmstadt, Technische Universität,
DOI: 10.25534/tuprints-00014184,
[Ph.D. Thesis]

L

Lampariello, Roberto (2021):
Optimal Motion Planning for Object Interception and Capture. (Publisher's Version)
Darmstadt, Technische Universität,
DOI: 10.26083/tuprints-00017617,
[Ph.D. Thesis]

Lioutikov, Rudolf (2018):
Parsing Motion and Composing Behavior for Semi-Autonomous Manipulation.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

Luck, Kevin Sebastian (2014):
Latent Space Reinforcement Learning.
Darmstadt, Technische Universität, [Bachelor Thesis]

M

Manschitz, Simon (2018):
Learning Sequential Skills for Robot Manipulation Tasks.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

Merfels, Christian (2014):
Large-scale probabilistic feature mapping and tracking for autonomous driving.
Darmstadt, Technische Universität, [Master Thesis]

Muelling, Katharina (2013):
Modeling and Learning of Complex Motor Tasks: A Case Study with Robot Table Tennis.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

P

Paraschos, Alexandros (2017):
Robot Skill Representation, Learning and Control with Probabilistic Movement Primitives.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

Parisi, Simone (2020):
Reinforcement Learning with Sparse and Multiple Rewards.
Darmstadt, Technische Universität,
DOI: 10.25534/tuprints-00011372,
[Ph.D. Thesis]

S

Sousa Ewerton, Marco Antonio (2020):
Bidirectional Human-Robot Learning: Imitation and Skill Improvement.
Darmstadt, Technische Universität,
DOI: 10.25534/tuprints-00011875,
[Ph.D. Thesis]

T

Tanneberg, Daniel (2020):
Understand-Compute-Adapt: Neural Networks for Intelligent Agents. (Publisher's Version)
Darmstadt, Technische Universität Darmstadt,
DOI: 10.25534/tuprints-00017234,
[Ph.D. Thesis]

Tosatto, Samuele (2021):
Off-Policy Reinforcement Learning for Robotics. (Publisher's Version)
Darmstadt, Technische Universität,
DOI: 10.26083/tuprints-00017536,
[Ph.D. Thesis]

V

Vinogradska, Julia (2018):
Gaussian Processes in Reinforcement Learning: Stability Analysis and Efficient Value Propagation.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

van Hoof, Herke (2016):
Machine Learning through Exploration for Perception-Driven Robotics.
Darmstadt, Technische Universität Darmstadt,
[Ph.D. Thesis]

W

Wang, Zhikun (2013):
Intention Inference and Decision Making with Hierarchical Gaussian Process Dynamics Models.
Darmstadt, Technische Universität,
[Ph.D. Thesis]

This list was generated on Fri May 7 14:47:59 2021 CEST.