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Language Models Can Reduce Asymmetry in Information Markets

Rahaman, N., Weiss, M., Wüthrich, M., Bengio, Y., Li, E., Pal, C., Schölkopf, B.

arXiv:2403.14443, March 2024, Published as: Redesigning Information Markets in the Era of Language Models, Conference on Language Modeling (COLM) (techreport)

Abstract
This work addresses the buyer's inspection paradox for information markets. The paradox is that buyers need to access information to determine its value, while sellers need to limit access to prevent theft. To study this, we introduce an open-source simulated digital marketplace where intelligent agents, powered by language models, buy and sell information on behalf of external participants. The central mechanism enabling this marketplace is the agents' dual capabilities: they not only have the capacity to assess the quality of privileged information but also come equipped with the ability to forget. This ability to induce amnesia allows vendors to grant temporary access to proprietary information, significantly reducing the risk of unauthorized retention while enabling agents to accurately gauge the information's relevance to specific queries or tasks. To perform well, agents must make rational decisions, strategically explore the marketplace through generated sub-queries, and synthesize answers from purchased information. Concretely, our experiments (a) uncover biases in language models leading to irrational behavior and evaluate techniques to mitigate these biases, (b) investigate how price affects demand in the context of informational goods, and (c) show that inspection and higher budgets both lead to higher quality outcomes.

ei

link (url) [BibTex]

link (url) [BibTex]


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Koopman Spectral Analysis Uncovers the Temporal Structure of Spontaneous Neural Events

Shao, K., Xu, Y., Logothetis, N., Shen, Z., Besserve, M.

Computational and Systems Neuroscience Meeting (COSYNE), March 2024 (poster)

ei

link (url) [BibTex]

link (url) [BibTex]


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Learning a Terrain- and Robot-Aware Dynamics Model for Autonomous Mobile Robot Navigation

Achterhold, J., Guttikonda, S., Kreber, J. U., Li, H., Stueckler, J.

CoRR abs/2409.11452, 2024, Preprint submitted to Robotics and Autonomous Systems Journal. https://arxiv.org/abs/2409.11452 (techreport) Submitted

Abstract
Mobile robots should be capable of planning cost-efficient paths for autonomous navigation. Typically, the terrain and robot properties are subject to variations. For instance, properties of the terrain such as friction may vary across different locations. Also, properties of the robot may change such as payloads or wear and tear, e.g., causing changing actuator gains or joint friction. Autonomous navigation approaches should thus be able to adapt to such variations. In this article, we propose a novel approach for learning a probabilistic, terrain- and robot-aware forward dynamics model (TRADYN) which can adapt to such variations and demonstrate its use for navigation. Our learning approach extends recent advances in meta-learning forward dynamics models based on Neural Processes for mobile robot navigation. We evaluate our method in simulation for 2D navigation of a robot with uni-cycle dynamics with varying properties on terrain with spatially varying friction coefficients. In our experiments, we demonstrate that TRADYN has lower prediction error over long time horizons than model ablations which do not adapt to robot or terrain variations. We also evaluate our model for navigation planning in a model-predictive control framework and under various sources of noise. We demonstrate that our approach yields improved performance in planning control-efficient paths by taking robot and terrain properties into account.

ev

preprint [BibTex]

preprint [BibTex]


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A Pontryagin Perspective on Reinforcement Learning

Eberhard, O., Vernade, C., Muehlebach, M.

Max Planck Institute for Intelligent Systems, 2024 (techreport)

lds

link (url) [BibTex]

link (url) [BibTex]


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Distributed Event-Based Learning via ADMM

Er, D., Trimpe, S., Muehlebach, M.

Max Planck Institute for Intelligent Systems, 2024 (techreport)

lds

link (url) [BibTex]

link (url) [BibTex]


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Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators

Baumeister, F., Mack, L., Stueckler, J.

CoRR abs/2409.13228, CoRR, 2024, Submitted to IEEE International Conference on Robotics and Automation (ICRA) 2025 (techreport) Submitted

Abstract
Few-shot adaptation is an important capability for intelligent robots that perform tasks in open-world settings such as everyday environments or flexible production. In this paper, we propose a novel approach for non-prehensile manipulation which iteratively adapts a physics-based dynamics model for model-predictive control. We adapt the parameters of the model incrementally with a few examples of robot-object interactions. This is achieved by sampling-based optimization of the parameters using a parallelizable rigid-body physics simulation as dynamic world model. In turn, the optimized dynamics model can be used for model-predictive control using efficient sampling-based optimization. We evaluate our few-shot adaptation approach in several object pushing experiments in simulation and with a real robot.

ev

preprint supplemental video link (url) [BibTex]

preprint supplemental video link (url) [BibTex]

2023


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Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures

Jenny, D.

ETH Zurich, Switzerland, November 2023, external supervision (thesis)

ei

[BibTex]

2023


[BibTex]


An Open-Source Modular Treadmill for Dynamic Force Measurement with Load Dependant Range Adjustment
An Open-Source Modular Treadmill for Dynamic Force Measurement with Load Dependant Range Adjustment

Sarvestani, A., Ruppert, F., Badri-Spröwitz, A.

2023 (unpublished) Submitted

Abstract
Ground reaction force sensing is one of the key components of gait analysis in legged locomotion research. To measure continuous force data during locomotion, we present a novel compound instrumented treadmill design. The treadmill is 1.7 m long, with a natural frequency of 170 Hz and an adjustable range that can be used for humans and small robots alike. Here, we present the treadmill’s design methodology and characterize it in its natural frequency, noise behavior and real-life performance. Additionally, we apply an ISO 376 norm conform calibration procedure for all spatial force directions and center of pressure position. We achieve a force accuracy of ≤ 5.6 N for the ground reaction forces and ≤ 13 mm in center of pressure position.

dlg

arXiv link (url) DOI [BibTex]


Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80
Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80

Berenz, V., Widmaier, F., Guist, S., Schölkopf, B., Büchler, D.

Robot Software Architectures Workshop (RSA) 2023, ICRA, 2023 (techreport)

Abstract
Robotic applications require the integration of various modalities, encompassing perception, control of real robots and possibly the control of simulated environments. While the state-of-the-art robotic software solutions such as ROS 2 provide most of the required features, flexible synchronization between algorithms, data streams and control loops can be tedious. o80 is a versatile C++ framework for robotics which provides a shared memory model and a command framework for real-time critical systems. It enables expert users to set up complex robotic systems and generate Python bindings for scientists. o80's unique feature is its flexible synchronization between processes, including the traditional blocking commands and the novel ``bursting mode'', which allows user code to control the execution of the lower process control loop. This makes it particularly useful for setups that mix real and simulated environments.

ei

arxiv poster link (url) [BibTex]

2022


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Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)

Biester, L., Demszky, D., Jin, Z., Sachan, M., Tetreault, J., Wilson, S., Xiao, L., Zhao, J.

Association for Computational Linguistics, December 2022 (proceedings)

ei

link (url) [BibTex]

2022


link (url) [BibTex]


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Proceedings of the First Conference on Causal Learning and Reasoning (CLeaR 2022)

Schölkopf, B., Uhler, C., Zhang, K.

177, Proceedings of Machine Learning Research, PMLR, April 2022 (proceedings)

ei

link (url) [BibTex]

link (url) [BibTex]


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Observability Analysis of Visual-Inertial Odometry with Online Calibration of Velocity-Control Based Kinematic Motion Models

Li, H., Stueckler, J.

abs/2204.06651, CoRR/arxiv, 2022 (techreport)

Abstract
In this paper, we analyze the observability of the visual-inertial odometry (VIO) using stereo cameras with a velocity-control based kinematic motion model. Previous work shows that in general case the global position and yaw are unobservable in VIO system, additionally the roll and pitch become also unobservable if there is no rotation. We prove that by integrating a planar motion constraint roll and pitch become observable. We also show that the parameters of the motion model are observable.

ev

link (url) [BibTex]

2021


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Proceedings of the 1st Workshop on NLP for Positive Impact

Field, A., Prabhumoye, S., Sap, M., Jin, Z., Zhao, J., Brockett, C.

Association for Computational Linguistics, August 2021 (proceedings)

ei

link (url) [BibTex]

2021


link (url) [BibTex]


Promoting metacognitive learning through systematic reflection
Promoting metacognitive learning through systematic reflection

Frederic Becker, , Lieder, F.

The first edition of Life Improvement Science Conference, June 2021 (poster)

Abstract
Human decision-making is sometimes systematically biased toward suboptimal decisions. For example, people often make short-sighted choices because they don't give enough weight to the long-term consequences of their actions. Previous studies showed that it is possible to overcome such biases by teaching people a more rational decision strategy through instruction, demonstrations, or practice with feedback. The benefits of these approaches tend to be limited to situations that are very similar to those used during the training. One way to overcome this limitation is to create general tools and strategies that people can use to improve their decision-making in any situation. Here we propose one such approach, namely directing people to systematically reflect on how they make their decisions. In systematic reflection, past experience is re-evaluated with the intention to learn. In this study, we investigate how reflection affects how people learn to plan and whether reflective learning can help people to discover more far-sighted planning strategies. In our experiment participants solve a series of 30 planning problems where the immediate rewards are smaller and therefore less important than long-term rewards. Building on Wolfbauer et al. (2020), the experimental group is guided by four reflection prompts asking the participant to describe their planning strategy, the strategy's performance, and his or her emotional response, insights, and intention to change their strategy. The control group practices planning without reflection prompts. Our pilot data suggest that systematic reflection helps people to more rapidly discover adaptive planning strategies. Our findings suggest that reflection is useful not only for helping people learn what to do in a specific situation but also for helping people learn how to think about what to do. In future work, we will compare the effects of different types of reflection on the subsequent changes in people's decision strategies. Developing apps that prompt people to reflect on their decisions may be a promising approach to accelerating cognitive growth and promoting lifelong learning.

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[BibTex]

[BibTex]


Toward a Science of Effective Well-Doing
Toward a Science of Effective Well-Doing

Lieder, F., Prentice, M., Corwin-Renner, E.

May 2021 (techreport)

Abstract
Well-doing, broadly construed, encompasses acting and thinking in ways that contribute to humanity’s flourishing in the long run. This often takes the form of setting a prosocial goal and pursuing it over an extended period of time. To set and pursue goals in a way that is extremely beneficial for humanity (effective well-doing), people often have to employ critical thinking and far-sighted, rational decision-making in the service of the greater good. To promote effective well-doing, we need to better understand its determinants and psychological mechanisms, as well as the barriers to effective well-doing and how they can be overcome. In this article, we introduce a taxonomy of different forms of well-doing and introduce a conceptual model of the cognitive mechanisms of effective well-doing. We view effective well-doing as the upper end of a moral continuum whose lower half comprises behaviors that are harmful to humanity (ill-doing), and we argue that the capacity for effective well-doing has to be developed through personal growth (e.g., learning how to pursue goals effectively). Research on these phenomena has so far been scattered across numerous disconnected literatures from multiple disciplines. To bring these communities together, we call for the establishment of a transdisciplinary research field focussed on understanding and promoting effective well-doing and personal growth as well as understanding and reducing ill-doing. We define this research field in terms of its goals and questions. We review what is already known about these questions in different disciplines and argue that laying the scientific foundation for promoting effective well-doing is one of the most valuable contributions that the behavioral sciences can make in the 21st century.

re

Preprint Project Page [BibTex]

2020


Towards Hybrid Active and Passive Compliant Mechanisms in Legged Robots
Towards Hybrid Active and Passive Compliant Mechanisms in Legged Robots

Milad Shafiee Ashtiani, A. A. S., Badri-Sproewitz, A.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, October 2020 (poster) Accepted

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Abstract Poster [BibTex]

2020


Abstract Poster [BibTex]


Optimal To-Do List Gamification
Optimal To-Do List Gamification

Stojcheski, J., Felso, V., Lieder, F.

ArXiv Preprint, 2020 (techreport)

Abstract
What should I work on first? What can wait until later? Which projects should I prioritize and which tasks are not worth my time? These are challenging questions that many people face every day. People’s intuitive strategy is to prioritize their immediate experience over the long-term consequences. This leads to procrastination and the neglect of important long-term projects in favor of seemingly urgent tasks that are less important. Optimal gamification strives to help people overcome these problems by incentivizing each task by a number of points that communicates how valuable it is in the long-run. Unfortunately, computing the optimal number of points with standard dynamic programming methods quickly becomes intractable as the number of a person’s projects and the number of tasks required by each project increase. Here, we introduce and evaluate a scalable method for identifying which tasks are most important in the long run and incentivizing each task according to its long-term value. Our method makes it possible to create to-do list gamification apps that can handle the size and complexity of people’s to-do lists in the real world.

re

link (url) DOI Project Page [BibTex]


VP above or below? A new perspective on the story of the virtual point
VP above or below? A new perspective on the story of the virtual point

Drama, Ö., Badri-Spröwitz, A.

Dynamic Walking, May 2020 (poster)

Abstract
The spring inverted pendulum model with an extended trunk (TSLIP) is widely used to investigate the postural stability in bipedal locomotion [1, 2]. The challenge of the model is to define a hip torque that generates feasible gait patterns while stabilizing the floating trunk. The virtual point (VP) method is proposed as a simplified solution, where the hip torque is coupled to the passive compliant leg force via a virtual point. This geometric coupling is based on the assumption that the instantaneous ground reaction forces of the stance phase (GRF) intersect at a single virtual point.

dlg

Poster Abstract link (url) [BibTex]

Poster Abstract link (url) [BibTex]


Viscous Damping in Legged Locomotion
Viscous Damping in Legged Locomotion

Mo, A., Izzi, F., Haeufle, D. F. B., Badri-Spröwitz, A.

Dynamic Walking, May 2020 (poster)

Abstract
Damping likely plays an essential role in legged animal locomotion, but remains an insufficiently understood mechanism. Intrinsic damping muscle forces can potentially add to the joint torque output during unexpected impacts, stabilise movements, convert the system’s energy, and reject unexpected perturbations.

dlg

Abstract Poster link (url) Project Page [BibTex]

Abstract Poster link (url) Project Page [BibTex]


How Quadrupeds Benefit from Lower Leg Passive Elasticity
How Quadrupeds Benefit from Lower Leg Passive Elasticity

Ruppert, F., Badri-Spröwitz, A.

Dynamic Walking, May 2020 (poster)

Abstract
Recently developed and fully actuated, legged robots start showing exciting locomotion capabilities, but rely heavily on high-power actuators, high-frequency sensors, and complex locomotion controllers. The engineering solutions implemented in these legged robots are much different compared to animals. Vertebrate animals share magnitudes slower neurocontrol signal velocities [1] compared to their robot counterparts. Also, animals feature a plethora of cascaded and underactuated passive elastic structures [2].

dlg

Abstract Poster link (url) Project Page [BibTex]


Potential for elastic soft tissue deformation and mechanosensory function within the lumbosacral spinal canal of birds
Potential for elastic soft tissue deformation and mechanosensory function within the lumbosacral spinal canal of birds

Kamska, V., Daley, M., Badri-Spröwitz, A.

Society for Integrative and Comparative Biology Annual Meeting (SICB Annual Meeting 2020), January 2020 (poster)

dlg

DOI [BibTex]

DOI [BibTex]


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25th International Symposium on Vision, Modeling and Visualization, VMV 2020
(Editors: Jens Krüger and Matthias Nießner and Jörg Stückler), Eurographics Association, 2020 (proceedings)

ev

[BibTex]

[BibTex]


Excursion Search for Constrained Bayesian Optimization under a Limited Budget of Failures
Excursion Search for Constrained Bayesian Optimization under a Limited Budget of Failures

Marco, A., Rohr, A. V., Baumann, D., Hernández-Lobato, J. M., Trimpe, S.

2020 (proceedings) In revision

Abstract
When learning to ride a bike, a child falls down a number of times before achieving the first success. As falling down usually has only mild consequences, it can be seen as a tolerable failure in exchange for a faster learning process, as it provides rich information about an undesired behavior. In the context of Bayesian optimization under unknown constraints (BOC), typical strategies for safe learning explore conservatively and avoid failures by all means. On the other side of the spectrum, non conservative BOC algorithms that allow failing may fail an unbounded number of times before reaching the optimum. In this work, we propose a novel decision maker grounded in control theory that controls the amount of risk we allow in the search as a function of a given budget of failures. Empirical validation shows that our algorithm uses the failures budget more efficiently in a variety of optimization experiments, and generally achieves lower regret, than state-of-the-art methods. In addition, we propose an original algorithm for unconstrained Bayesian optimization inspired by the notion of excursion sets in stochastic processes, upon which the failures-aware algorithm is built.

am ics

arXiv code (python) PDF [BibTex]

2019


ProtoGAN: Towards Few Shot Learning for Action Recognition
ProtoGAN: Towards Few Shot Learning for Action Recognition

Dwivedi, S. K., Gupta, V., Mitra, R., Ahmed, S., Jain, A.

Proc. International Conference on Computer Vision (ICCV) Workshops, October 2019 (manual)

Abstract
Few-shot learning (FSL) for action recognition is a challenging task of recognizing novel action categories which are represented by few instances in the training data. In a more generalized FSL setting (G-FSL), both seen as well as novel action categories need to be recognized. Conventional classifiers suffer due to inadequate data in FSL setting and inherent bias towards seen action categories in G-FSL setting. In this paper, we address this problem by proposing a novel ProtoGAN framework which synthesizes additional examples for novel categories by conditioning a conditional generative adversarial network with class prototype vectors. These class prototype vectors are learnt using a Class Prototype Transfer Network (CPTN) from examples of seen categories. Our synthesized examples for a novel class are semantically similar to real examples belonging to that class and is used to train a model exhibiting better generalization towards novel classes. We support our claim by performing extensive experiments on three datasets: UCF101, HMDB51 and Olympic-Sports. To the best of our knowledge, we are the first to report the results for G-FSL and provide a strong benchmark for future research. We also outperform the state-of-the-art method in FSL for all the aforementioned datasets.

ps

paper data [BibTex]

2019


paper data [BibTex]


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Perception of temporal dependencies in autoregressive motion

Meding, K., Schölkopf, B., Wichmann, F. A.

Perception, 48(2-suppl):141, 42nd European Conference on Visual Perception (ECVP), August 2019 (poster)

ei

link (url) [BibTex]

link (url) [BibTex]


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Phenomenal Causality and Sensory Realism

Bruijns, S. A., Meding, K., Schölkopf, B., Wichmann, F. A.

Perception, 48(2-suppl):141, 42nd European Conference on Visual Perception (ECVP), August 2019 (poster)

ei

link (url) [BibTex]

link (url) [BibTex]


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Automatic Segmentation and Labelling for Robot Table Tennis Time Series

Lutz, P.

Technical University Darmstadt, Germany, August 2019 (thesis)

ei

[BibTex]

[BibTex]


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Neural mass modeling of the Ponto-Geniculo-Occipital wave and its neuromodulation

Shao, K., Logothetis, N., Besserve, M.

28th Annual Computational Neuroscience Meeting (CNS*2019), July 2019 (poster)

ei

DOI [BibTex]

DOI [BibTex]


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Demo Abstract: Fast Feedback Control and Coordination with Mode Changes for Wireless Cyber-Physical Systems

(Best Demo Award)

Mager, F., Baumann, D., Jacob, R., Thiele, L., Trimpe, S., Zimmerling, M.

Proceedings of the 18th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), pages: 340-341, 18th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), April 2019 (poster)

ics

arXiv PDF DOI [BibTex]

arXiv PDF DOI [BibTex]


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Fluctuating interface with a pinning potential

Pranjić, Daniel

Universität Stuttgart, Stuttgart, 2019 (thesis)

icm

[BibTex]

[BibTex]


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Controlling pattern formation in the confined Schnakenberg model

Beyer, David Bernhard

Universität Stuttgart, Stuttgart, 2019 (thesis)

icm

[BibTex]

[BibTex]


HPLC separation of ligand-exchanged gold clusters with atomic precision
HPLC separation of ligand-exchanged gold clusters with atomic precision

Itzigehl, Selina

Univ. of Stuttgart, 2019 (thesis)

pf

[BibTex]

[BibTex]

2018


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Poster Abstract: Toward Fast Closed-loop Control over Multi-hop Low-power Wireless Networks

Mager, F., Baumann, D., Trimpe, S., Zimmerling, M.

Proceedings of the 17th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), pages: 158-159, Porto, Portugal, April 2018 (poster)

ics

DOI Project Page [BibTex]

2018


DOI Project Page [BibTex]


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Representation of sensory uncertainty in macaque visual cortex

Goris, R., Henaff, O., Meding, K.

Computational and Systems Neuroscience (COSYNE) 2018, March 2018 (poster)

ei

[BibTex]

[BibTex]


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Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform

Ma, L., Stueckler, J., Wu, T., Cremers, D.

arxiv, 2018, arXiv:1808.01834 (techreport)

ev

[BibTex]

[BibTex]


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Pattern forming systems under confinement

Maihöfer, Michael

Universität Stuttgart, Stuttgart, 2018 (thesis)

icm

[BibTex]

[BibTex]


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Electrostatic interaction between colloids with constant surface potentials at fluid interfaces

Bebon, Rick

Universität Stuttgart, Stuttgart, 2018 (thesis)

icm

[BibTex]


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Generalized phase locking analysis of electrophysiology data

Safavi, S., Panagiotaropoulos, T., Kapoor, V., Logothetis, N. K., Besserve, M.

7th AREADNE Conference on Research in Encoding and Decoding of Neural Ensembles, 2018 (poster)

ei

link (url) [BibTex]

link (url) [BibTex]


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Non-equilibrium dynamics of a binary solvent around heated colloidal particles

Wilke, Moritz

Universität Stuttgart, Stuttgart, 2018 (thesis)

icm

[BibTex]

[BibTex]


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Monte Carlo study of colloidal structure formation at fluid interfaces

Meiler, Tim

Universität Stuttgart, Stuttgart, 2018 (thesis)

icm

[BibTex]

[BibTex]