@INPROCEEDINGS{Metzen:EWRL:2012:OGAHC,
title = {Online Skill Discovery using Graph-based Clustering},
booktitle = {10th European Workshop on Reinforcement Learning, (EWRL 2012)},
author = {Jan Hendrik Metzen},
url = {http://www.informatik.uni-bremen.de/~jhm/files/ewrl_2012_ogahc.pdf},
pages = {},
month = JUN,
year = {2012},
location = {Edinburgh, Scotland},
abstract = {We introduce a new online skill discovery method for reinforcement learning in
discrete domains. The method is based on the bottleneck principle and identifies
skills using a bottom-up hierarchical clustering of the estimated transition
graph. In contrast to prior clustering approaches, it can be used
incrementally and thus several times during the learning process. Our empirical
evaluation shows that ``assuming high connectivity in the face of uncertainty''
can prevent premature identification of skills. Furthermore, we show that the
choice of the linkage criterion is crucial for dealing with non-random sampling
policies and stochastic environments.}
}
@INPROCEEDINGS{Metzen:EWRL:2012:MBEPS,
title = {Model-based Evolutionary Policy Search for Skill Learning in Continuous Domains},
booktitle = {10th European Workshop on Reinforcement Learning, (EWRL 2012)},
author = {Jan Hendrik Metzen},
url = {http://www.informatik.uni-bremen.de/~jhm/files/ewrl_2012_mbeps_poster.pdf},
pages = {},
month = JUN,
year = {2012},
location = {Edinburgh, Scotland}
}
@INPROCEEDINGS{Straube:Neuroscience:2011,
month = NOV,
year = {2011},
title = {Choosing an Appropriate Performance Measure: Classification of {EEG}-Data with Varying Class Distribution},
booktitle = {Proceedings of the 41st Meeting of the Society for Neuroscience 2011},
location = {Washington DC, United States},
author = {Sirko Straube and Jan Hendrik Metzen and Anett Seeland and Mario Krell and Elsa Andrea Kirchner}
}
@INPROCEEDINGS{Metzen:GFKL:2011,
title = {Rapid Adaptation of Brain Reading Interfaces based on Threshold Adjustment},
booktitle = {Proceedings of the 2011 Conference of the German Classification Society, (GfKl-2011)},
author = {Jan Hendrik Metzen and Elsa Andrea Kirchner},
url = {http://www.informatik.uni-bremen.de/~jhm/files/gfkl_2011_abstract.pdf},
pages = {138},
month = AUG,
year = {2011},
location = {Frankfurt, Germany}
}
@INPROCEEDINGS{Metzen:DAGM:2011,
author = {Jan Hendrik Metzen and {Su-Kyoung} Kim and Elsa Andrea Kirchner},
title = {Minimizing Calibration Time for Brain Reading},
booktitle = {Pattern Recognition},
series = {Lecture Notes in Computer Science},
publisher = {Springer Berlin / Heidelberg},
isbn = {978-3-642-23122-3},
url = {http://www.informatik.uni-bremen.de/~jhm/files/DAGM_2011.pdf},
pages = {366--375},
volume = {6835},
month = AUG,
year = {2011},
publisher = {Springer},
location = {Heidelberg, Germany},
note = {The original publication is available at www.springerlink.com under http://www.springerlink.com/content/731775n33wg062w2/fulltext.pdf},
abstract = {Machine learning is increasingly used to autonomously adapt brain-machine
interfaces to user-specific brain patterns. In order to
minimize the
preparation time of the system, it is highly desirable to reduce the length of
the calibration procedure, during which training data is acquired from the user,
to a minimum. One recently proposed approach is to reuse models that have been
trained in historic usage sessions of the same or other users by utilizing an
ensemble-based approach. In this work, we propose two extensions of this
approach which are based on the idea to combine predictions made by
the historic ensemble with session-specific predictions that become available
once a small amount of training data has been collected. These extensions are
particularly useful for Brain Reading Interfaces (BRIs), a specific kind
of brain-machine interfaces. BRIs do not require that user
feedback is given and thus, additional training data may be acquired
concurrently to the usage session. Accordingly, BRIs should initially
perform well when only a small amount of training data acquired in a
short calibration procedure is available and allow an increased performance
when more training data becomes available during the usage session. An
empirical offline-study in a testbed for the use of BRIs to support robotic
telemanipulation shows that the proposed extensions allow to achieve this
kind of behavior.}
}
@INPROCEEDINGS{Metzen:SSP:2011,
title = {On Transferring Spatial Filters in a Brain Reading Scenario},
booktitle = {Statistical Signal Processing Workshop (SSP), 2011 IEEE},
author = {Jan Hendrik Metzen and Su Kyoung Kim and Timo Duchrow and Elsa Andrea Kirchner and Frank Kirchner},
isbn = {978-1-4577-0569-4},
pages = {797--800},
month = JUN,
year = {2011},
abstract = {Machine learning approaches are increasingly used in brain-machine-interfaces to
allow automatic adaptation to user-specific brain
patterns. One of the most crucial factors for the practical success of these
systems is that this adaptation can be achieved with a minimum amount of
training data since training data needs to be recorded during a
calibration procedure prior to the actual usage session. To this end, one
promising approach is to reuse models based on data recorded in preceding
sessions of the same or of other users. In this paper, we investigate
under which conditions it is favorable to reuse models (more specifically
spatial filters) trained on data from historic sessions compared to learning new
spatial filters on the current session's calibration data. We present an
empirical study in a scenario in which Brain Reading, a particular kind of
brain-machine-interface, is used to support robotic telemanipulation.}
}
@INPROCEEDINGS{Kirchner:ISAIRAS:2010,
title = {Towards Operator Monitoring via Brain Reading - An {EEG-based} Approach for Space Applications},
booktitle = {Proceedings of the 10th International Symposium on Artificial Intelligence, Robotics and Automation in Space {(iSAIRAS-10)}},
author = {Elsa Andrea Kirchner and Hendrik W\"{o}hrle and Constantin Bergatt and {Su-Kyoung} Kim and Jan Hendrik Metzen and David Feess and Frank Kirchner},
month = SEP,
year = {2010},
pages = {448--455},
url = {http://www.dfki.de/web/research/ric/publications/renameFileForDownload?filename=110722_Towards%20Operator%20Monitoring%20via%20Brain%20Reading%20-%20An%20EEG-based%20Approach_iSAIRAS_EKirchner.pdf&file_id=uploads_1087}
}
@INPROCEEDINGS{Metzen:AAMAS:2010,
address = {Richland, {SC}},
series = {{AAMAS} '10},
title = {Model-based direct policy search},
isbn = {978-0-9826571-1-9},
location = {Toronto, Canada},
url = {http://portal.acm.org/citation.cfm?id=1838206.1838495},
booktitle = {Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
author = {Jan Hendrik Metzen and Frank Kirchner},
year = {2010},
pages = {1589--1590}
}
@ARTICLE{Metzen:KI:2009,
title = {Learning to Play the {BRIO} Labyrinth Game},
volume = {Themenheft Reinforcement Learning},
journal = {Zeitschrift f\"{u}r K\"{u}nstliche Intelligenz},
author = {Jan Hendrik Metzen and Elsa Andrea Kirchner and Larbi Abdenebaoui and Frank Kirchner},
year = {2009},
pages = {34--37},
url = {http://www.kuenstliche-intelligenz.de/fileadmin/template/main/archiv/pdf/ki2009-03_page34_web_teaser.pdf}
}
@ARTICLE{Metzen:IVC:2009,
title = {Matching of anatomical tree structures for registration of medical images},
volume = {27},
issn = {0262-8856},
url = {http://dx.doi.org/10.1016/j.imavis.2008.04.002},
doi = {10.1016/j.imavis.2008.04.002},
number = {7},
journal = {Image and Vision Computing},
author = {Jan Hendrik Metzen and Tim Kr\"{o}ger and Andrea Schenk and Stephan Zidowitz and {Heinz-Otto} Peitgen and Xiaoyi Jiang},
month = JUN,
year = {2009},
pages = {923--933},
abstract = {Many medical applications require a registration of different images of the same organ. In many cases, such a registration is accomplished by manual placement of landmarks in the images. In this paper we propose a method which is able to find reasonable landmarks automatically. To achieve this, bifurcations of the vessel systems, which have been extracted from the images by a segmentation algorithm, are assigned by the so-called association graph method and the coordinates of these matched bifurcations can be used as landmarks for a non-rigid registration algorithm. Several constraints to be used in combination with the association graph method are proposed and evaluated on a ground truth consisting of anatomical trees from liver and lung. Furthermore, a method for preprocessing (tree pruning) as well as for postprocessing (clique augmentation) are proposed and evaluated on this ground truth. The proposed method achieves promising results for anatomical trees of liver and lung and for medical images obtained with different modalities and at different points in time.}
}
@INPROCEEDINGS{Bergatt:LEMIR:2009,
address = {Bled, Slovenia},
title = {Quantification and Minimization of the {Simulation-Reality-Gap} on a {BRIO} Labyrinth Game},
booktitle = {Proceedings of the first International Workshop on Learning and Data Mining for Robotics {(LEMIR-09)}},
author = {Constantin Bergatt and Jan Hendrik Metzen and Elsa Andrea Kirchner and Frank Kirchner},
year = {2009}
}
@INPROCEEDINGS{Kirchner:MLRTA:2009,
address = {Paderborn},
title = {Assisting Telemanipulation Operators via {Real-Time} Brain Reading},
isbn = {1869-2087},
url = {http://robotik.dfki-bremen.de/fileadmin/CONTENT/Forschung/Projekte/underwater/VI-Bot/Kirchner_Assisting_Telemanipulation_Operators_via_BR_FINAL.pdf},
booktitle = {Lemgoer Schriftenreihe zur industriellen Informationstechnik},
author = {Elsa Andrea Kirchner and Jan Hendrik Metzen and Timo Duchrow and Su Kyong Kim and Frank Kirchner},
month = SEP,
year = {2009}
}
@INCOLLECTION{Kassahun:CIARS:2009,
title = {Incremental Acquisition of Neural Structures through Evolution},
url = {http://dx.doi.org/10.1007/978-3-540-89933-4_10},
booktitle = {Design and Control of Intelligent Robotic Systems},
author = {Yohannes Kassahun and Jan Hendrik Metzen and Mark Edgington and Frank Kirchner},
year = {2009},
pages = {187--208}
}
@INPROCEEDINGS{Metzen:PPSN:2008,
title = {Evolving Neural Networks for Online Reinforcement Learning},
url = {http://dx.doi.org/10.1007/978-3-540-87700-4_52},
booktitle = {Parallel Problem Solving from Nature -- {PPSN} X},
author = {Jan Hendrik Metzen and Mark Edgington and Yohannes Kassahun and Frank Kirchner},
month = SEP,
year = {2008},
pages = {518--527},
abstract = {For many complex Reinforcement Learning problems with large and continuous state spaces, neuroevolution (the evolution of artificial neural networks) has achieved promising results. This is especially true when there is noise in sensor and/or actuator signals. These results have mainly been obtained in offline learning settings, where the training and evaluation phase of the system are separated. In contrast, in online Reinforcement Learning tasks where the actual performance of the systems during its learning phase matters, the results of neuroevolution are significantly impaired by its purely exploratory nature, meaning that it does not use (i.e. exploit) its knowledge of the performance of single individuals in order to improve its performance during learning. In this paper we describe modifications which significantly improve the online performance of the neuroevolutionary method Evolutionary Acquisition of Neural Topologies (EANT) and discuss the results obtained on two benchmark problems.}
}
@INPROCEEDINGS{Roemmermann:PPSN:2008,
title = {Learning Walking Patterns for Kinematically Complex Robots Using Evolution Strategies},
url = {http://dx.doi.org/10.1007/978-3-540-87700-4_108},
booktitle = {Parallel Problem Solving from Nature -- {PPSN} X},
author = {Malte R\"{o}mmermann and Mark Edgington and Jan Hendrik Metzen and Jose de Gea and Yohannes Kassahun and Frank Kirchner},
year = {2008},
pages = {1091--1100}
}
@INPROCEEDINGS{Kassahun:GECCO:2008,
address = {New York, {NY,} {USA}},
title = {Accelerating neuroevolutionary methods using a Kalman filter},
isbn = {978-1-60558-130-9},
location = {Atlanta, {GA,} {USA}},
url = {http://dx.doi.org/10.1145/1389095.1389365},
booktitle = {{GECCO} '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation},
publisher = {{ACM}},
author = {Yohannes Kassahun and Jose de Gea and Mark Edgington and Jan Hendrik Metzen and Frank Kirchner},
year = {2008},
pages = {1397--1404}
}
@INPROCEEDINGS{Metzen:GECCO:2008,
address = {New York, {NY,} {USA}},
title = {Towards efficient online reinforcement learning using neuroevolution},
isbn = {978-1-60558-130-9},
location = {Atlanta, {GA,} {USA}},
url = {http://dx.doi.org/10.1145/1389095.1389371},
series = {{GECCO} '08},
booktitle = {Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation},
publisher = {{ACM}},
author = {Jan Hendrik Metzen and Frank Kirchner and Mark Edgington and Yohannes Kassahun},
year = {2008},
pages = {1425--1426}
}
@INPROCEEDINGS{Metzen:AAMAS:2008,
address = {Richland, {SC}},
title = {Analysis of an evolutionary reinforcement learning method in a multiagent domain},
isbn = {978-0-9817381-0-9},
location = {Estoril, Portugal},
url = {http://portal.acm.org/citation.cfm?id=1402428},
series = {{AAMAS} '08},
booktitle = {Proceedings of the 7th International Conference on Autonomous Agents and Multiagent Systems},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
author = {Jan Hendrik Metzen and Mark Edgington and Yohannes Kassahun and Frank Kirchner},
month = MAY,
year = {2008},
pages = {291--298},
abstract = {Many multiagent problems comprise subtasks which can be considered as reinforcement learning (RL) problems. In addition to classical temporal difference methods, evolutionary algorithms are among the most promising approaches for such RL problems. The relative performance of these approaches in certain subdomains (e.\,g. multiagent learning) of the general RL problem remains an open question at this time. In addition to theoretical analysis, benchmarks are one of the most important tools for comparing different RL methods in certain problem domains. A recently proposed multiagent RL benchmark problem is the RoboCup Keepaway benchmark. This benchmark is one of the most challenging multiagent learning problems because its state-space is continuous and high dimensional, and both the sensors and the actuators are noisy. In this paper we analyze the performance of the neuroevolutionary approach called Evolutionary Acquisition of Neural Topologies (EANT) in the Keepaway benchmark, and compare the results obtained using EANT with the results of other algorithms tested on the same benchmark.}
}
@INPROCEEDINGS{Metzen:ICMLA:2007,
address = {Washington, {DC,} {USA}},
title = {Performance Evaluation of {EANT} in the {RoboCup} Keepaway Benchmark},
isbn = {0-7695-3069-9},
url = {http://dx.doi.org/10.1109/ICMLA.2007.80},
booktitle = {{ICMLA} '07: Proceedings of the Sixth International Conference on Machine Learning and Applications},
publisher = {{IEEE} Computer Society},
author = {Jan Hendrik Metzen and Mark Edgington and Yohannes Kassahun and Frank Kirchner},
year = {2007},
pages = {342--347}
}
@INPROCEEDINGS{Kassahun:GECCO:2007,
address = {New York, {NY,} {USA}},
title = {A common genetic encoding for both direct and indirect encodings of networks},
isbn = {978-1-59593-697-4},
location = {London, England},
url = {http://dx.doi.org/10.1145/1276958.1277162},
booktitle = {{GECCO} '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation},
publisher = {{ACM}},
author = {Yohannes Kassahun and Mark Edgington and Jan H Metzen and Gerald Sommer and Frank Kirchner},
month = JUL,
year = {2007},
pages = {1029--1036}
}
@INPROCEEDINGS{Kassahun:KI:2007,
title = {A General Framework for Encoding and Evolving Neural Networks},
url = {http://dx.doi.org/10.1007/978-3-540-74565-5_17},
booktitle = {{KI} 2007: Advances in Artificial Intelligence},
author = {Yohannes Kassahun and Jan Metzen and Jose de Gea and Mark Edgington and Frank Kirchner},
year = {2007},
pages = {205--219},
address = {Osnabr{\"u}ck, Germany}
}
@INPROCEEDINGS{Metzen:GBR:2007,
address = {Alicante, Spain},
title = {Matching of Tree Structures for Registration of Medical Images},
url = {http://dx.doi.org/10.1007/978-3-540-72903-7_2},
booktitle = {{Graph-Based} Representations in Pattern Recognition},
publisher = {Springer Verlag},
author = {Jan Metzen and Tim Kr\"{o}ger and Andrea Schenk and Stephan Zidowitz and {Heinz-Otto} Peitgen and Xiaoyi Jiang},
year = {2007},
pages = {13--24},
abstract = {Many medical applications require a registration of different images of the same organ. In many cases, such a registration is accomplished by manually placing landmarks in the images. In this paper we propose a method which is able to find reasonable landmarks automatically. To achieve this, nodes of the vessel systems, which have been extracted from the images by a segmentation algorithm, will be assigned by the so-called association graph method and the coordinates of these matched nodes can be used as landmarks for a non-rigid registration algorithm.}
}
@INPROCEEDINGS{Metzen:BVM:2007,
title = {Matching von Baumstrukturen - Zuordnung von Gef\"{a}{\ss}systemen aus Leber und Lunge},
url = {http://dx.doi.org/10.1007/978-3-540-71091-2_24},
booktitle = {Bildverarbeitung f\"{u}r die Medizin 2007},
author = {Jan Hendrik Metzen and Tim Kr\"{o}ger and Andrea Schenk and Stephan Zidowitz and {Heinz-Otto} Peitgen and Xiaoyi Jiang},
month = {March},
year = {2007},
pages = {116--120}
}
@MASTERSTHESIS{Metzen:DA:2006,
author = {Jan Hendrik Metzen},
month = {July},
year = {2006},
title = {Matching von {B}aumstrukturen in der medizinischen {B}ildverarbeitung},
school = {Westf{\"a}lische Wilhelms-Universit{\"a}t M{\"u}nster},
month = {July},
url = {http://www.informatik.uni-bremen.de/~jhm/files/Matching_von_Baumstrukturen.pdf}
}
@INPROCEEDINGS{Mueller:ACE:2005,
author = {Jens M{\"u}ller and Jan Hendrik Metzen and Alexander Ploss and Maraike Schellmann and Sergei Gorlatch},
title = {Rokkatan: Scaling an {RTS} Game Design to the Massively Multiplayer Realm},
booktitle = {ACM SIGHCHI International Conference on Advances in Computer Entertainment Technology (ACE 05)},
pages = {125--132},
year = {2005},
month = {June},
address = {Valencia, Spain},
publisher = {ACM},
url = {http://pvs.uni-muenster.de/pvs/mitarbeiter/jmueller/rokkatan.pdf}
}
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