Publications | Max Planck Institute for Intelligent Systems

553 results (View BibTeX file of all listed publications)

2024

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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]

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]

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Interpreting How Large Language Models Handle Facts and Counterfactuals through Mechanistic Interpretability

Ortu, F.

University of Trieste, Italy, March 2024 (mastersthesis)

ei

ei Ortu, F. Interpreting How Large Language Models Handle Facts and Counterfactuals through Mechanistic Interpretability University of Trieste, Italy, March 2024 (mastersthesis)

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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.

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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]

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A Pontryagin Perspective on Reinforcement Learning

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

Max Planck Institute for Intelligent Systems, 2024 (techreport)

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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]

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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]

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

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]

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

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Denoising Representation Learning for Causal Discovery

Sakenyte, U.

Université de Genèva, Switzerland, December 2023, external supervision (mastersthesis)

ei

2023

ei Sakenyte, U. Denoising Representation Learning for Causal Discovery Université de Genèva, Switzerland, December 2023, external supervision (mastersthesis)

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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

ei Jenny, D. Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures ETH Zurich, Switzerland, November 2023, external supervision (thesis)

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Efficient Sampling from Differentiable Matrix Elements

Technical University of Munich, Germany, September 2023 (mastersthesis)

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ei Kofler, A. Efficient Sampling from Differentiable Matrix Elements Technical University of Munich, Germany, September 2023 (mastersthesis)

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Intrinsic complexity and mechanisms of expressivity of cortical neurons

University of Tübingen, Germany, March 2023 (mastersthesis)

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ei Spieler, A. M. Intrinsic complexity and mechanisms of expressivity of cortical neurons University of Tübingen, Germany, March 2023 (mastersthesis)

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CausalEffect Estimation by Combining Observational and Interventional Data

ETH Zurich, Switzerland, February 2023 (mastersthesis)

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lds ei Kladny, K. CausalEffect Estimation by Combining Observational and Interventional Data ETH Zurich, Switzerland, February 2023 (mastersthesis)

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Towards Generative Machine Teaching

Qui, Z.

Technical University of Munich, Germany, February 2023 (mastersthesis)

ei

ei Qui, Z. Towards Generative Machine Teaching Technical University of Munich, Germany, February 2023 (mastersthesis)

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ArchiSound: Audio Generation with Diffusion

Schneider, F.

ETH Zurich, Switzerland, January 2023, external supervision (mastersthesis)

ei

ei Schneider, F. ArchiSound: Audio Generation with Diffusion ETH Zurich, Switzerland, January 2023, external supervision (mastersthesis)

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Generation and Quantification of Spin in Robot Table Tennis

University of Stuttgart, Germany, January 2023 (mastersthesis)

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ei Dittrich, A. Generation and Quantification of Spin in Robot Table Tennis University of Stuttgart, Germany, January 2023 (mastersthesis)

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Natural Language Processing for Policymaking

Jin, Z., Mihalcea, R.

In Handbook of Computational Social Science for Policy, pages: 141-162, 7, (Editors: Bertoni, E. and Fontana, M. and Gabrielli, L. and Signorelli, S. and Vespe, M.), Springer International Publishing, 2023 (inbook)

ei

ei Jin, Z., Mihalcea, R. Natural Language Processing for Policymaking In Handbook of Computational Social Science for Policy, pages: 141-162, 7, (Editors: Bertoni, E. and Fontana, M. and Gabrielli, L. and Signorelli, S. and Vespe, M.), Springer International Publishing, 2023 (inbook)

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]

ei Berenz, V., Widmaier, F., Guist, S., Schölkopf, B., Büchler, D. Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80 Robot Software Architectures Workshop (RSA) 2023, ICRA, 2023 (techreport)

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

ei Biester, L., Demszky, D., Jin, Z., Sachan, M., Tetreault, J., Wilson, S., Xiao, L., Zhao, J. Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI) Association for Computational Linguistics, December 2022 (proceedings)

link (url) [BibTex]

Magnetic Micro-/Nanopropellers for Biomedicine

Magnetic Micro-/Nanopropellers for Biomedicine

Qiu, T., Jeong, M., Goyal, R., Kadiri, V., Sachs, J., Fischer, P.

In Field-Driven Micro and Nanorobots for Biology and Medicine, pages: 389-410, 16, (Editors: Sun, Y. and Wang, X. and Yu, J.), Springer, Cham, 2022 (inbook)

Abstract

In nature, many bacteria swim by rotating their helical flagella. A particularly promising class of artificial micro- and nano-robots mimic this propeller-like propulsion mechanism to move through fluids and tissues for applications in minimally-invasive medicine. Several fundamental challenges have to be overcome in order to build micro-machines that move similar to bacteria for in vivo applications. Here, we review recent advances of magnetically-powered micro-/nano-propellers. Four important aspects of the propellers – the geometrical shape, the fabrication method, the generation of magnetic fields for actuation, and the choice of biocompatible magnetic materials – are highlighted. First, the fundamental requirements are elucidated that arise due to hydrodynamics at low Reynolds (Re) number. We discuss the role that the propellers’ shape and symmetry play in realizing effective propulsion at low Re. Second, the additive nano-fabrication method Glancing Angle Deposition is discussed as a versatile technique to quickly grow large numbers of designer nano-helices. Third, systems to generate rotating magnetic fields via permanent magnets or electromagnetic coils are presented. And finally, the biocompatibility of the magnetic materials is discussed. Iron-platinum is highlighted due to its biocompatibility and its superior magnetic properties, which is promising for targeted delivery, minimally-invasive magnetic nano-devices and biomedical applications.

pf

link (url) DOI [BibTex]

pf Qiu, T., Jeong, M., Goyal, R., Kadiri, V., Sachs, J., Fischer, P. Magnetic Micro-/Nanopropellers for Biomedicine In Field-Driven Micro and Nanorobots for Biology and Medicine, pages: 389-410, 16, (Editors: Sun, Y. and Wang, X. and Yu, J.), Springer, Cham, 2022 (inbook)

link (url) DOI [BibTex]

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Life Improvement Science

Lieder, F., Prentice, M.

In Encyclopedia of Quality of Life and Well-Being Research, Springer, November 2022 (inbook)

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re Lieder, F., Prentice, M. Life Improvement Science In Encyclopedia of Quality of Life and Well-Being Research, Springer, November 2022 (inbook)

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Investigating Independent Mechanisms in Neural Networks

Université Paris-Saclay, France, October 2022 (mastersthesis)

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ei Liang, W. Investigating Independent Mechanisms in Neural Networks Université Paris-Saclay, France, October 2022 (mastersthesis)

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Modeling subgroup differences in fMRI data: disentangling subgroup-specific responses from shared ones

ETH Zurich, Switzerland, October 2022 (mastersthesis)

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ei Keidar, D. Modeling subgroup differences in fMRI data: disentangling subgroup-specific responses from shared ones ETH Zurich, Switzerland, October 2022 (mastersthesis)

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Multi-Target Multi-Object Manipulation using Relational Deep Reinforcement Learning

Feil, M.

Technnical University Munich, Germany, September 2022 (mastersthesis)

ei

ei Feil, M. Multi-Target Multi-Object Manipulation using Relational Deep Reinforcement Learning Technnical University Munich, Germany, September 2022 (mastersthesis)

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Independent Mechanism Analysis for High Dimensions

University of Tübingen, Germany, September 2022, (Graduate Training Centre of Neuroscience) (mastersthesis)

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ei Sliwa, J. Independent Mechanism Analysis for High Dimensions University of Tübingen, Germany, September 2022, (Graduate Training Centre of Neuroscience) (mastersthesis)

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On the Adversarial Robustness of Causal Algorithmic Recourse

Dominguez-Olmedo, R.

University of Tübingen, Germany, August 2022 (mastersthesis)

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ei Dominguez-Olmedo, R. On the Adversarial Robustness of Causal Algorithmic Recourse University of Tübingen, Germany, August 2022 (mastersthesis)

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Independent Mechanism Analysis in High-Dimensional Observation Spaces

ETH Zurich, Switzerland, June 2022 (mastersthesis)

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ei Ghosh, S. Independent Mechanism Analysis in High-Dimensional Observation Spaces ETH Zurich, Switzerland, June 2022 (mastersthesis)

Learning Plastic Matching of Robot Dynamics in Closed-Loop Central Pattern Generators: Data

Learning Plastic Matching of Robot Dynamics in Closed-Loop Central Pattern Generators: Data

Ruppert, F., Badri-Spröwitz, A.

Edmond, May 2022 (techreport)

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link (url) DOI [BibTex]

dlg Ruppert, F., Badri-Spröwitz, A. Learning Plastic Matching of Robot Dynamics in Closed-Loop Central Pattern Generators: Data Edmond, May 2022 (techreport)

link (url) DOI [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]

ei Schölkopf, B., Uhler, C., Zhang, K. Proceedings of the First Conference on Causal Learning and Reasoning (CLeaR 2022) 177, Proceedings of Machine Learning Research, PMLR, April 2022 (proceedings)

link (url) [BibTex]

Data for BirdBot Achieves Energy-Efﬁcient Gait with Minimal Control Using Avian-Inspired Leg Clutching

Data for BirdBot Achieves Energy-Efﬁcient Gait with Minimal Control Using Avian-Inspired Leg Clutching

Badri-Spröwitz, A., Sarvestani, A. A., Sitti, M., Daley, M. A.

Edmond, March 2022 (techreport)

dlg pi

DOI Project Page [BibTex]

dlg pi Badri-Spröwitz, A., Sarvestani, A. A., Sitti, M., Daley, M. A. Data for BirdBot Achieves Energy-Efﬁcient Gait with Minimal Control Using Avian-Inspired Leg Clutching Edmond, March 2022 (techreport)

DOI Project Page [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]

ev Li, H., Stueckler, J. Observability Analysis of Visual-Inertial Odometry with Online Calibration of Velocity-Control Based Kinematic Motion Models abs/2204.06651, CoRR/arxiv, 2022 (techreport)

link (url) [BibTex]

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Causal Models for Dynamical Systems

Peters, J., Bauer, S., Pfister, N.

In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 671-690, 1, Association for Computing Machinery, 2022 (inbook)

ei

arXiv DOI [BibTex]

ei Peters, J., Bauer, S., Pfister, N. Causal Models for Dynamical Systems In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 671-690, 1, Association for Computing Machinery, 2022 (inbook)

arXiv DOI [BibTex]

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Towards Causal Algorithmic Recourse

Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I.

In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 139-166, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

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ei plg Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I. Towards Causal Algorithmic Recourse In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 139-166, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

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CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations

Salewski, L., Koepke, A. S., Lensch, H. P. A., Akata, Z.

In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 69-88, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

ei

ei Salewski, L., Koepke, A. S., Lensch, H. P. A., Akata, Z. CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 69-88, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

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Causality for Machine Learning

In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 765-804, 1, Association for Computing Machinery, New York, NY, USA, 2022 (inbook)

ei

arXiv DOI [BibTex]

ei Schölkopf, B. Causality for Machine Learning In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 765-804, 1, Association for Computing Machinery, New York, NY, USA, 2022 (inbook)

arXiv DOI [BibTex]

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Voltage dependent investigations on the spin polarization of layered heterostructues

Miller, M.

Universität Stuttgart, Stuttgart, 2022 (mastersthesis)

mms

mms Miller, M. Voltage dependent investigations on the spin polarization of layered heterostructues Universität Stuttgart, Stuttgart, 2022 (mastersthesis)

2021

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Learning Neural Causal Models with Active Interventions

ETH Zurich, Switzerland, November 2021 (mastersthesis)

ei

2021

ei Scherrer, N. Learning Neural Causal Models with Active Interventions ETH Zurich, Switzerland, November 2021 (mastersthesis)

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HealthGen: Conditional Generation of Realistic Medical Time Series with Informative Missingness

ETH Zurich, Switzerland, October 2021 (mastersthesis)

ei

ei Bing, S. HealthGen: Conditional Generation of Realistic Medical Time Series with Informative Missingness ETH Zurich, Switzerland, October 2021 (mastersthesis)

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Study of the Interventional Consistency of Autoencoders

Lanzillotta, G.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

ei

ei Lanzillotta, G. Study of the Interventional Consistency of Autoencoders ETH Zurich, Switzerland, October 2021 (mastersthesis)

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Training with Few to Manipulate Many. On OOD generalization in relational reinforcement learning

ETH Zurich, Switzerland, October 2021 (mastersthesis)

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ei Mambelli, D. Training with Few to Manipulate Many. On OOD generalization in relational reinforcement learning ETH Zurich, Switzerland, October 2021 (mastersthesis)

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Electriflow: Augmenting Books With Tangible Animation Using Soft Electrohydraulic Actuators

Purnendu, , Novack, S., Acome, E., Alistar, M., Keplinger, C., Gross, M. D., Bruns, C., Leithinger, D.

In ACM SIGGRAPH 2021 Labs, pages: 1-2, Association for Computing Machinery, SIGGRAPH 2021, August 2021 (inbook)

Abstract

We present Electriflow: a method of augmenting books with tangible animation employing soft electrohydraulic actuators. These actuators are compact, silent and fast in operation, and can be fabricated with commodity materials. They generate an immediate hydraulic force upon electrostatic activation without an external fluid supply source, enabling a simple and self-contained design. Electriflow actuators produce an immediate shape transition from flat to folded state which enabled their seamless integration into books. For the Emerging Technologies exhibit, we will demonstrate the prototype of a book augmented with the capability of tangible animation.

rm

Supplemental Material link (url) DOI [BibTex]

rm Purnendu, , Novack, S., Acome, E., Alistar, M., Keplinger, C., Gross, M. D., Bruns, C., Leithinger, D. Electriflow: Augmenting Books With Tangible Animation Using Soft Electrohydraulic Actuators In ACM SIGGRAPH 2021 Labs, pages: 1-2, Association for Computing Machinery, SIGGRAPH 2021, August 2021 (inbook)

Supplemental Material link (url) DOI [BibTex]

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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]

ei Field, A., Prabhumoye, S., Sap, M., Jin, Z., Zhao, J., Brockett, C. Proceedings of the 1st Workshop on NLP for Positive Impact Association for Computational Linguistics, August 2021 (proceedings)

link (url) [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]

re Lieder, F., Prentice, M., Corwin-Renner, E. Toward a Science of Effective Well-Doing May 2021 (techreport)

Preprint Project Page [BibTex]

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Robotic Surgery Training in AR: Multimodal Record and Replay

Krauthausen, F.

pages: 1-147, University of Stuttgart, Stuttgart, May 2021, Study Program in Software Engineering (mastersthesis)

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hi Krauthausen, F. Robotic Surgery Training in AR: Multimodal Record and Replay pages: 1-147, University of Stuttgart, Stuttgart, May 2021, Study Program in Software Engineering (mastersthesis)

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Direct detection of spin Hall effect induced torques in platinum/ferromagnetic bilayer systems

Universität Stuttgart, Stuttgart, January 2021 (mastersthesis)

mms

mms Alten, F. Direct detection of spin Hall effect induced torques in platinum/ferromagnetic bilayer systems Universität Stuttgart, Stuttgart, January 2021 (mastersthesis)

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Method of making one or more fibrils, computer implemented method of simulating an adhesive force of one or more fibrils and fibril

Sitti, M., Liimatainen, V.

2021, EP Prio. Patent App. 21 162 253.5 (mpi_year_book)

pi

pi Sitti, M., Liimatainen, V. Method of making one or more fibrils, computer implemented method of simulating an adhesive force of one or more fibrils and fibril 2021, EP Prio. Patent App. 21 162 253.5 (mpi_year_book)

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Community detection in heterogeneously attributed networks

Politecnico di Torino, 2021 (mastersthesis)

pio

link (url) [BibTex]

pio Zottino, N. Community detection in heterogeneously attributed networks Politecnico di Torino, 2021 (mastersthesis)

link (url) [BibTex]

Scientific Report 2016 - 2021

Scientific Report 2016 - 2021

2021 (mpi_year_book)

Abstract

This report presents research done at the Max Planck Institute for Intelligent Systems from January2016 to November 2021. It is our fourth report since the founding of the institute in 2011. Dueto the fact that the upcoming evaluation is an extended one, the report covers a longer reportingperiod.This scientific report is organized as follows: we begin with an overview of the institute, includingan outline of its structure, an introduction of our latest research departments, and a presentationof our main collaborative initiatives and activities (Chapter1). The central part of the scientificreport consists of chapters on the research conducted by the institute’s departments (Chapters2to6) and its independent research groups (Chapters7 to24), as well as the work of the institute’scentral scientific facilities (Chapter25). For entities founded after January 2016, the respectivereport sections cover work done from the date of the establishment of the department, group, orfacility. These chapters are followed by a summary of selected outreach activities and scientificevents hosted by the institute (Chapter26). The scientific publications of the featured departmentsand research groups published during the 6-year review period complete this scientific report.

ei hi ps pi rm

Scientific Report 2016 - 2021 [BibTex]

ei hi ps pi rm Scientific Report 2016 - 2021 2021 (mpi_year_book)

Scientific Report 2016 - 2021 [BibTex]

2020

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Voltage dependent interfacial magnetism in multilayer systems

Universität Stuttgart, Stuttgart, December 2020 (thesis)

mms

2020

mms Nacke, R. Voltage dependent interfacial magnetism in multilayer systems Universität Stuttgart, Stuttgart, December 2020 (thesis)

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Hydromagnonics: Manipulation of magnonic systems with hydrogen

Universität Stuttgart, Stuttgart, December 2020 (mastersthesis)

mms

mms Sauter, R. Hydromagnonics: Manipulation of magnonic systems with hydrogen Universität Stuttgart, Stuttgart, December 2020 (mastersthesis)

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A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Ahmed, O.

ETH Zurich, Switzerland, October 2020 (mastersthesis)

ei

ei Ahmed, O. A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning ETH Zurich, Switzerland, October 2020 (mastersthesis)

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A Comprehensive Benchmark Evaluation of Synthetic Data Generation for Biomedical Imaging

DuMont Schütte, A.

ETH Zurich, Switzerland, October 2020 (mastersthesis)

ei

ei DuMont Schütte, A. A Comprehensive Benchmark Evaluation of Synthetic Data Generation for Biomedical Imaging ETH Zurich, Switzerland, October 2020 (mastersthesis)

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