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2017


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On the Design of LQR Kernels for Efficient Controller Learning

Marco, A., Hennig, P., Schaal, S., Trimpe, S.

Proceedings of the 56th IEEE Annual Conference on Decision and Control (CDC), pages: 5193-5200, IEEE, IEEE Conference on Decision and Control, December 2017 (conference)

Abstract
Finding optimal feedback controllers for nonlinear dynamic systems from data is hard. Recently, Bayesian optimization (BO) has been proposed as a powerful framework for direct controller tuning from experimental trials. For selecting the next query point and finding the global optimum, BO relies on a probabilistic description of the latent objective function, typically a Gaussian process (GP). As is shown herein, GPs with a common kernel choice can, however, lead to poor learning outcomes on standard quadratic control problems. For a first-order system, we construct two kernels that specifically leverage the structure of the well-known Linear Quadratic Regulator (LQR), yet retain the flexibility of Bayesian nonparametric learning. Simulations of uncertain linear and nonlinear systems demonstrate that the LQR kernels yield superior learning performance.

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arXiv PDF On the Design of LQR Kernels for Efficient Controller Learning - CDC presentation DOI Project Page [BibTex]

2017


arXiv PDF On the Design of LQR Kernels for Efficient Controller Learning - CDC presentation DOI Project Page [BibTex]


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Optimal gamification can help people procrastinate less

Lieder, F., Griffiths, T. L.

Annual Meeting of the Society for Judgment and Decision Making, Annual Meeting of the Society for Judgment and Decision Making, November 2017 (conference)

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Project Page [BibTex]

Project Page [BibTex]


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Optimizing Long-term Predictions for Model-based Policy Search

Doerr, A., Daniel, C., Nguyen-Tuong, D., Marco, A., Schaal, S., Toussaint, M., Trimpe, S.

Proceedings of 1st Annual Conference on Robot Learning (CoRL), 78, pages: 227-238, (Editors: Sergey Levine and Vincent Vanhoucke and Ken Goldberg), 1st Annual Conference on Robot Learning, November 2017 (conference)

Abstract
We propose a novel long-term optimization criterion to improve the robustness of model-based reinforcement learning in real-world scenarios. Learning a dynamics model to derive a solution promises much greater data-efficiency and reusability compared to model-free alternatives. In practice, however, modelbased RL suffers from various imperfections such as noisy input and output data, delays and unmeasured (latent) states. To achieve higher resilience against such effects, we propose to optimize a generative long-term prediction model directly with respect to the likelihood of observed trajectories as opposed to the common approach of optimizing a dynamics model for one-step-ahead predictions. We evaluate the proposed method on several artificial and real-world benchmark problems and compare it to PILCO, a model-based RL framework, in experiments on a manipulation robot. The results show that the proposed method is competitive compared to state-of-the-art model learning methods. In contrast to these more involved models, our model can directly be employed for policy search and outperforms a baseline method in the robot experiment.

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PDF Project Page [BibTex]

PDF Project Page [BibTex]


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Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers

Doerr, A., Nguyen-Tuong, D., Marco, A., Schaal, S., Trimpe, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 5295-5301, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

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PDF arXiv DOI Project Page [BibTex]

PDF arXiv DOI Project Page [BibTex]


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Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization

Marco, A., Berkenkamp, F., Hennig, P., Schoellig, A. P., Krause, A., Schaal, S., Trimpe, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 1557-1563, IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017 (inproceedings)

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PDF arXiv ICRA 2017 Spotlight presentation Virtual vs. Real - Video explanation DOI Project Page [BibTex]

PDF arXiv ICRA 2017 Spotlight presentation Virtual vs. Real - Video explanation DOI Project Page [BibTex]


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A reward shaping method for promoting metacognitive learning

Lieder, F., Krueger, P. M., Callaway, F., Griffiths, T. L.

In Proceedings of the Third Multidisciplinary Conference on Reinforcement Learning and Decision-Making, 2017 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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The moderating role of arousal on the seductive detail effect

Schneider, S., Wirzberger, M., Augustin, Y., Rey, G. D.

In Abstracts of the 59th Conference of Experimental Psychologists (TeaP), pages: 96, Papst Science Publishers, Lengerich, 2017 (inproceedings)

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[BibTex]

[BibTex]


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Influences of cognitive load on learning performance, speech and physiological parameters in a dual-task setting

Wirzberger, M., Herms, R., Esmaeili Bijarsari, S., Rey, G. D., Eibl, M.

In Abstracts of the 20th Conference of the European Society for Cognitive Psychology, pages: 161, Potsdam, Germany, 2017 (inproceedings)

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[BibTex]

[BibTex]


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Time – Space – Content? Interrupting features of hyperlinks in multimedia learning

Wirzberger, M., Schneider, S., Dlouhy, S., Rey, G. D.

In Abstracts of the 59th Conference of Experimental Psychologists (TeaP), pages: 97, Pabst Science Publishers, Lengerich, 2017 (inproceedings)

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[BibTex]

[BibTex]


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Computer Science meets Cognition: Möglichkeiten und Herausforderungen interdisziplinärer Kognitionsforschung [Computer science meets cognition: Chances and challenges in interdisciplinary research on cognition]

Wirzberger, M., Truschzinski, M., Schmidt, R., Barlag, M.

In INFORMATIK 2017, Lecture Notes in Informatics (LNI), pages: 2273-2277, Gesellschaft für Informatik, Bonn, 2017 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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When does bounded-optimal metareasoning favor few cognitive systems?

Milli, S., Lieder, F., Griffiths, T. L.

In AAAI Conference on Artificial Intelligence, 31, 2017 (inproceedings)

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[BibTex]

[BibTex]


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The Structure of Goal Systems Predicts Human Performance

Bourgin, D., Lieder, F., Reichman, D., Talmon, N., Griffiths, T.

In Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017 (inproceedings)

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[BibTex]

[BibTex]


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Learning to (mis) allocate control: maltransfer can lead to self-control failure

Bustamante, L., Lieder, F., Musslick, S., Shenhav, A., Cohen, J.

In The 3rd Multidisciplinary Conference on Reinforcement Learning and Decision Making. Ann Arbor, Michigan, 2017 (inproceedings)

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[BibTex]

[BibTex]


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Inspecting cognitive load factors in digital learning settings with ACT-R

Wirzberger, M.

In Dagstuhl 2017. Proceedings of the 11th Joint Workshop of the German Research Training Groups in Computer Science, pages: 62, 2017 (inproceedings)

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[BibTex]

[BibTex]


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Lernförderliche Gestaltung computerbasierter Instruktionen zur Roboterkonstruktion [Enhancing design of computer-based instructions in a robot construction task]

Esmaeili Bijarsari, S., Wirzberger, M., Rey, G. D.

In INFORMATIK 2017, Lecture Notes in Informatics (LNI), pages: 2279-2286, Gesellschaft für Informatik, Bonn, 2017 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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An automatic method for discovering rational heuristics for risky choice

Lieder, F., Krueger, P. M., Griffiths, T. L.

In Proceedings of the 39th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society, 2017 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Mouselab-MDP: A new paradigm for tracing how people plan

Callaway, F., Lieder, F., Krueger, P. M., Griffiths, T. L.

In The 3rd multidisciplinary conference on reinforcement learning and decision making, 2017 (inproceedings)

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[BibTex]

[BibTex]


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A dynamic process model for predicting workload in an air traffic controller task

Truschzinski, M., Wirzberger, M.

In Proceedings of the 39th Annual Meeting of the Cognitive Science Society, pages: 1224-1229, Cognitive Science Society, Austin, TX, 2017 (inproceedings)

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link (url) [BibTex]

link (url) [BibTex]


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Auswirkung systeminduzierter Delays auf die menschliche Gedächtnisleistung in einem virtuellen agentenbasierten Trainingssetting [Influence of system-induced delays on human memory performance in a virtual agent-based training scenario]

Wirzberger, M., Schmidt, R., Rey, G. D., Hardt, W.

In INFORMATIK 2017, Lecture Notes in Informatics (LNI), pages: 2287-2294, Gesellschaft für Informatik, Bonn, 2017 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Enhancing metacognitive reinforcement learning using reward structures and feedback

Krueger, P. M., Lieder, F., Griffiths, T. L.

In Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017 (inproceedings)

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Project Page Project Page [BibTex]

Project Page Project Page [BibTex]


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Helping people choose subgoals with sparse pseudo rewards

Callaway, F., Lieder, F., Griffiths, T. L.

In Proceedings of the Third Multidisciplinary Conference on Reinforcement Learning and Decision Making, 2017 (inproceedings)

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[BibTex]

[BibTex]


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Modeling cognitive load effects in an interrupted learning task: An ACT-R approach

Wirzberger, M., Rey, G. D., Krems, J.

In Proceedings of the 39th Annual Meeting of the Cognitive Science Society, pages: 3540-3545, Cognitive Science Society, Austin, TX, 2017 (inproceedings)

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link (url) [BibTex]

link (url) [BibTex]

2013


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Learned helplessness and generalization

Lieder, F., Goodman, N. D., Huys, Q. J. M.

In 35th Annual Conference of the Cognitive Science Society, 2013 (inproceedings)

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[BibTex]

2013


[BibTex]


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Reverse-Engineering Resource-Efficient Algorithms

Lieder, F., Goodman, N. D., Griffiths, T. L.

In NIPS Workshop Resource-Efficient Machine Learning, 2013 (inproceedings)

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[BibTex]

[BibTex]


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Attention impairment in multimedia learning: Does initial task attention act as moderator

Wirzberger, M., Rey, G. D.

In Media Psychology: Media Research: Yesterday, Today, and Tomorrow. Proceedings of the 8th Conference of the Media Psychology Division of the German Psychological Society, pages: 11, University of Würzburg, Würzburg, 2013 (inproceedings)

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[BibTex]

[BibTex]


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Inducing impaired attention within the seductive detail effect: Do already distracted learners suffer more?

Wirzberger, M., Rey, G. D.

In Abstracts of the 55th Conference of Experimental Psychologists, pages: 314, Pabst Science Publishers, Lengerich, 2013 (inproceedings)

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[BibTex]

[BibTex]


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Controllability and resource-rational planning.

Lieder, F., Goodman, N. D., Huys, Q. J. M.

In Computational and Systems Neuroscience (Cosyne), pages: 112, 2013 (inproceedings)

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[BibTex]

[BibTex]

2007


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Less Conservative Polytopic LPV Models for Charge Control by Combining Parameter Set Mapping and Set Intersection

Kwiatkowski, A., Trimpe, S., Werner, H.

In Proceedings of the 46th IEEE Conference on Decision and Control, 2007 (inproceedings)

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DOI [BibTex]

2007


DOI [BibTex]