Publications | Max Planck Institute for Intelligent Systems

270 results (View BibTeX file of all listed publications)

2024

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.

link (url) [BibTex]

2024

ei Rahaman, N., Weiss, M., Wüthrich, M., Bengio, Y., Li, E., Pal, C., Schölkopf, B. Language Models Can Reduce Asymmetry in Information Markets arXiv:2403.14443, March 2024, Published as: Redesigning Information Markets in the Era of Language Models, Conference on Language Modeling (COLM) (techreport)

link (url) [BibTex]

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.

preprint [BibTex]

ev Achterhold, J., Guttikonda, S., Kreber, J. U., Li, H., Stueckler, J. Learning a Terrain- and Robot-Aware Dynamics Model for Autonomous Mobile Robot Navigation CoRR abs/2409.11452, 2024, Preprint submitted to Robotics and Autonomous Systems Journal. https://arxiv.org/abs/2409.11452 (techreport) Submitted

preprint [BibTex]

A Pontryagin Perspective on Reinforcement Learning

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

Max Planck Institute for Intelligent Systems, 2024 (techreport)

lds

link (url) [BibTex]

lds Eberhard, O., Vernade, C., Muehlebach, M. A Pontryagin Perspective on Reinforcement Learning Max Planck Institute for Intelligent Systems, 2024 (techreport)

link (url) [BibTex]

Distributed Event-Based Learning via ADMM

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

Max Planck Institute for Intelligent Systems, 2024 (techreport)

lds

link (url) [BibTex]

lds Er, D., Trimpe, S., Muehlebach, M. Distributed Event-Based Learning via ADMM Max Planck Institute for Intelligent Systems, 2024 (techreport)

link (url) [BibTex]

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.

preprint supplemental video link (url) [BibTex]

ev Baumeister, F., Mack, L., Stueckler, J. Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators CoRR abs/2409.13228, CoRR, 2024, Submitted to IEEE International Conference on Robotics and Automation (ICRA) 2025 (techreport) Submitted

preprint supplemental video link (url) [BibTex]

2023

Fairness in Machine Learning: Limitations and Opportunities

Barocas, S., Hardt, M., Narayanan, A.

MIT Press, December 2023 (book)

Abstract

An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning. Fairness and Machine Learning introduces advanced undergraduate and graduate students to the intellectual foundations of this recently emergent field, drawing on a diverse range of disciplinary perspectives to identify the opportunities and hazards of automated decision-making. It surveys the risks in many applications of machine learning and provides a review of an emerging set of proposed solutions, showing how even well-intentioned applications may give rise to objectionable results. It covers the statistical and causal measures used to evaluate the fairness of machine learning models as well as the procedural and substantive aspects of decision-making that are core to debates about fairness, including a review of legal and philosophical perspectives on discrimination. This incisive textbook prepares students of machine learning to do quantitative work on fairness while reflecting critically on its foundations and its practical utility.• Introduces the technical and normative foundations of fairness in automated decision-making• Covers the formal and computational methods for characterizing and addressing problems• Provides a critical assessment of their intellectual foundations and practical utility• Features rich pedagogy and extensive instructor resources

link (url) [BibTex]

2023

sf Barocas, S., Hardt, M., Narayanan, A. Fairness in Machine Learning: Limitations and Opportunities MIT Press, December 2023 (book)

link (url) [BibTex]

Hydraulically Amplified Self-healing Electrostatic Actuators

Keplinger, C. M., Acome, E. L., Kellaris, N. A., Mitchell, S. K.

(US Patent 11795979B2), October 2023 (patent)

Abstract

An electro-hydraulic actuator includes a deformable shell defining an enclosed internal cavity and containing a liquid dielectric, first and second electrodes on first and second sides, respectively, of the enclosed internal cavity. An electrostatic force between the first and second electrodes upon application of a voltage to one of the electrodes draws the electrodes towards each other to displace the liquid dielectric within the enclosed internal cavity. The shell includes active and inactive areas such that the electrostatic forces between the first and second electrodes displaces the liquid dielectric within the enclosed internal cavity from the active area of the shell to the inactive area of the shell. The first and second electrodes, the deformable shell, and the liquid dielectric cooperate to form a self-healing capacitor, and the liquid dielectric is configured for automatically filling breaches in the liquid dielectric resulting from dielectric breakdown.

link (url) [BibTex]

rm Keplinger, C. M., Acome, E. L., Kellaris, N. A., Mitchell, S. K. Hydraulically Amplified Self-healing Electrostatic Actuators (US Patent 11795979B2), October 2023 (patent)

link (url) [BibTex]

High Strain Peano Hydraulically Amplified Self-Healing Electrostatic (HASEL) Transducers

Keplinger, C. M., Wang, X., Mitchell, S. K.

(US Patent App. 18/138,621), August 2023 (patent)

Abstract

High strain hydraulically amplified self-healing electrostatic transducers having increased maximum theoretical and practical strains are disclosed. In particular, the actuators include electrode configurations having a zipping front created by the attraction of the electrodes that is configured orthogonally to a strain axis along which the actuators. This configuration produces increased strains. In turn, various form factors for the actuator configuration are presented including an artificial circular muscle and a strain amplifying pulley system. Other actuator configurations are contemplated that include independent and opposed electrode pairs to create cyclic activation, hybrid electrode configurations, and use of strain limiting layers for controlled deflection of the actuator.

link (url) [BibTex]

rm Keplinger, C. M., Wang, X., Mitchell, S. K. High Strain Peano Hydraulically Amplified Self-Healing Electrostatic (HASEL) Transducers (US Patent App. 18/138,621), August 2023 (patent)

link (url) [BibTex]

Capacitive Self-Sensing for Electrostatic Transducers with High Voltage Isolation

Correll, N., Ly, K. D., Kellaris, N. A., Keplinger, C. M.

(US Patent App. 17/928,453), June 2023 (patent)

Abstract

Transducer systems disclosed herein include self-sensing capabilities. In particular, electrostatic transducers include a low voltage electrode and a high voltage electrode. A low voltage sensing unit is coupled with the low voltage electrode of the electrostatic transducer. The low voltage sensing unit is configured to measure a capacitance of the electrostatic transducer, from which displacement of the electrostatic transducer may be calculated. High voltage drive signals received by the high voltage electrode during actuation may be isolated from the low voltage sensing unit. The isolation may be provided by dielectric material of the electrostatic transducer, a voltage suppression component, and/or a voltage suppression module comprising a low impedance ground path. In the event of an electrical failure of the transducer, the low voltage sensing unit may be isolated from high voltages.

link (url) [BibTex]