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Neural Implicit k-space for Binning-Free Non-Cartesian Cardiac MR Imaging 28th

Neural Implicit k-Space for Binning-Free Non-Cartesian Cardi...

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28th International conference on Information processing in Medical Imaging (IPMI)

作者： Huang, Wenqi Li, Hongwei Bran Pan, Jiazhen Cruz, Gastao Rueckert, Daniel Hammernik, Kerstin Tech Univ Munich Munich Germany Univ Zurich Zurich Switzerland Univ Michigan Ann Arbor MI USA Imperial Coll London Dept Comp London England

ISBN: (纸本)9783031340475;9783031340482

In this work, we propose a novel image reconstruction framework that directly learns a neural implicit representation in k-space for ECG-triggered non-Cartesian Cardiac Magnetic Resonance Imaging (CMR). While existing methods bin acquired data from neighboring time points to reconstruct one phase of the cardiac motion, our framework allows for a continuous, binning-free, and subject-specific k-space representation. We assign a unique coordinate that consists of time, coil index, and frequency domain location to each sampled k-space point. We then learn the subject-specific mapping from these unique coordinates to k-space intensities using a multi-layer perceptron with frequency domain regularization. During inference, we obtain a complete k-space for Cartesian coordinates and an arbitrary temporal resolution. A simple inverse Fourier transform recovers the image, eliminating the need for density compensation and costly non-uniform Fourier transforms for non-Cartesian data. This novel imaging framework was tested on 42 radially sampled datasets from 6 subjects. The proposed method outperforms other techniques qualitatively and quantitatively using data from four and one heartbeat(s) and 30 cardiac phases. Our results for one heartbeat reconstruction of 50 cardiac phases show improved artifact removal and spatio-temporal resolution, leveraging the potential for real-time CMR. (Code available: https://***/wenqihuang/NIK MRI).

关键词： Image Reconstruction Non-Cartesian MRI Cardiac MRI Neural Implicit Functions Deep Learning k-space Interpolation

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handling MEG data Corrupted with Deep Brain Stimulation Artifacts - Some Pointers

Handling MEG Data Corrupted with Deep Brain Stimulation Arti...

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Advances in Electrical, Electronics and Computational Intelligence (ICAEECI), International conference on

作者： Suranjita Ganguly Ankita Jain Aditya Koppula Sreedev Sasidharan Vamsi Vijay Mohan Dattada Andreas Højlund Kousik Sarathy Sridharan Dept. of Biomedical Engineering Indian Institute of Technology Hyderabad Hyderabad India Department of Linguistics Cognitive Science and Semiotics Aarhus University Aarhus Denmark Dept. of Biomedical Engineering Dept. of Heritage Science and Technology Indian Institute of Technology Hyderabad Hyderabad India

Deep brain stimulation (DBS) is a therapeutic treatment used in pathological conditions, which is known to improve clinical state, but the effect-mechanisms are unclear. The electrophysiological study of effect-mechanisms is complicated by strong artifactual components blurring the boundary between brain activity and DBS-induced noise. To study the artifactual signatures and the effect of pre-processing steps such as spatiotemporal signal space separation (tSSS) and normalization on the DBS-corrupted MEG data, we deployed a watermelon-based phantom ‘implanted’ with DBS leads and stimulated the phantom with various DBS stimulation settings. We observe that tSSS can lead to a ‘spillover’ of artifacts between sensor types and bipolar stimulation leads to lower sub-harmonic (20 Hz) artifacts compared to monopolar stimulation. Normalized spectra, we show here, can be biased if artifactual spectral bins are chosen as the normalizing factor. Alternatively, artifact-free bins can be visually chosen or an unbiased approach such as the FOOOF method can be used.

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FPGA Implementation of Efficient 2D-FFT Beamforming for On-Board processing in Satellites

FPGA Implementation of Efficient 2D-FFT Beamforming for On-B...

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IEEE conference on Vehicular Technology (VTC)

作者： Rakesh Palisetty Geoffrey Eappen Vibhum Singh Luis Manuel Garces Socarras Vu Nguyen Ha Juan A. Vásquez-Peralvo Jorge Luis Gonzalez Rios Juan Carlos Merlano Duncan Wallace Alves Martins Symeon Chatzinotas Björn Ottersten Adem Coskun Stephen King Salvatore D’Addio Piero Angeletti Interdisciplinary Centre for Security Reliability and Trust University of Luxembourg Luxembourg Institut Supérieur de l’Aéronautique et de l’Espace (ISAE-SUPAERO) Université de Toulouse France European Space Agency

On-board processing of digital beamforming in satellites is an efficient solution for the higher data rates, more capacity, and lower latency, but the available on-board limited power makes it impractical to digitally create thousands of beams at once. A significant portion of the analog hardware in a satellite communications payload can be replaced with highly integrated digital components, which are often more affordable, lighter, smaller, and reprogrammable by employing digital beamforming. In comparison to matrix-by-vector multiplication beamforming, the discrete Fourier transform (DFT) beamformer enables the finer realization of real-time beamformers with reduced circuit complexity and lower power consumption. Fast Fourier transform (FFT) methods can further reduce the computing cost of the DFT computation. Therefore, in this paper, area-power efficient two-dimensional (2D) FFT digital beamforming techniques are analyzed and implemented. The major implementation challenge is to produce N samples per cycle with lower area-power consumption. Fully unrolled 4-bit twiddle factor (TF) quantized FFT is proposed in this regard. The optimization techniques through quantization, truncation, and complex multipliers are thoroughly discussed for efficient implementation. The behavioral and post-route timing simulations are validated, and implementation results like area and power consumption are estimated and compared among conventional , fully unrolled, and the proposed 4-bit TF quantized 2D-FFT.

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Multi scale histogram-based intrusion detection system for the MIL-STD-1553 protocol

Multi scale histogram-based intrusion detection system for t...

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Communications and Networking (MeditCom), IEEE International Mediterranean conference on

作者： Gianmarco Baldini European Commission Joint Research Centre Ispra Italy

In recent years, there is a growing interest by the research community in the development of countermeasures to cybersecurity attacks to serial bus networks in different domains including the industrial sector (e.g., SCADA), vehicular systems (CAN-BUS) and other domains. This paper focuses specifically to the protection of the serial buses used in the aerospace sector (e.g., aircrafts, satellite systems) and the MIL-STD-1553 in particular. The MIL-STD-1553 protocol is commonly used in the aerospace sector in order to communicate information across the components of aerospace systems and supports spacecraft on-board data handling (OBDH) subsystems, both military and civil. This paper proposes an intrusion detection systems (IDS) to detect attacks by analyzing the MIL-STD-1553 traffic using machine learning algorithms. Taking in consideration that the platforms, where the MIL-STD-1553 protocol is deployed, have limited computing resources in comparison to large ICT infrastructures where IDS is usually implemented, the objective is to design a IDS which is computing efficient. This paper proposes an IDS based on the specific coding of MIL-STD-1553 messages to words, whose frequency is analyzed using histograms. A novel multi-scale histogram IDS, where sequence of words are also analyzed, is used to widen the feature space, which is then optimized using the ReliefF algorithm to identify the most discriminating features. The approach manages to obtain a 96% attack detection accuracy on a recent MIL-STD-1553 public data set outperforming other IDS approaches from literature based on entropy measures.

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Wavelet denoising method for improving the accuracy of attitude determination in miniaturized space applications

Wavelet denoising method for improving the accuracy of attit...

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International conference on System Theory, Control, and Computing (ICSTCC)

作者： Bianca Gabriela Antofie Cristian Vidan Carmen-Ioana Bogliş Ciprian-Marius Larco Teodor Lucian Grigorie Military Technical Academy “Ferdinand I” Faculty of Aircraft and Military Vehicles Bucharest Romania Faculty of Aerospace Engineering University Politehnica of Bucharest Bucharest Romania

This paper presents a new approach for improving the attitude determination precision of small satellite systems by filtering the data acquired from their MEMS (Micro-Electro-Mechanical Systems) inertial sensors. The growth in the global space sector requires innovative solutions that can guarantee the successful integration of emerging technologies. While miniaturization may appear ideal for space missions because of the reduction in dimension and cost, the enhanced sensitivity to external factors usually compromises the accuracy of navigation information. The core of this research lies in finding a way to preserve the valuable attitude information from the noise-corrupted signals provided by a cluster of MEMS gyros. The proposed method for processing the perturbed signals was the powerful tool of wavelet multiresolution analysis (WMRA). The procedure was software implemented with the help of MATLAB apps Simulink and Wavelet Analyzer which ensured the implementation of a gyro model, an attitude determination algorithm and the wavelet decomposition of the simulated signals. To fully validate the use of wavelets in enhancing attitude estimation, the study was conducted in two distinct phases: local and global validation. The results of the simulations showed the effectiveness of each wavelet function and level of decomposition for noise reduction and attitude angles accuracy improvement

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Resting State Brain Connectivity Analysis from EEG and FNIRS Signals 23rd

Resting State Brain Connectivity Analysis from EEG and FNI...

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23rd International conference on Computational Science, ICCS 2023

作者： Blanco, Rosmary Koba, Cemal Crimi, Alessandro Sano Centre for Computational Medicine Computer Vision Data Science Team Krakow Poland

ISBN: (纸本)9783031360206

Contemporary neuroscience is highly focused on the synergistic use of machine learning and network analysis. Indeed, network neuroscience analysis intensively capitalizes on clustering metrics and statistical tools. In this context, the integrated analysis of functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) provides complementary information about the electrical and hemodynamic activity of the brain. Evidence supports the mechanism of the neurovascular coupling mediates brain processing. However, it is not well understood how the specific patterns of neuronal activity are represented by these techniques. Here we have investigated the topological properties of functional networks of the resting-state brain between synchronous EEG and fNIRS connectomes, across frequency bands, using source space analysis, and through graph theoretical approaches. We observed that at global-level analysis small-world topology network features for both modalities. The edge-wise analysis pointed out increased inter-hemispheric connectivity for oxy-hemoglobin compared to EEG, with no differences across the frequency bands. Our results show that graph features extracted from fNIRS can reflect both short- and long-range organization of neural activity, and that is able to characterize the large-scale network in the resting state. Further development of integrated analyses of the two modalities is required to fully benefit from the added value of each modality. However, the present study highlights that multimodal source space analysis approaches can be adopted to study brain functioning in healthy resting states, thus serving as a foundation for future work during tasks and in pathology, with the possibility of obtaining novel comprehensive biomarkers for neurological diseases. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Brain

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Performance of the image persistence model for Euclid infrared detectors 11

Performance of the image persistence model for Euclid infrar...

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conference on X-Ray, Optical, and Infrared Detectors for Astronomy XI

作者： Kubik, B. Barbier, R. Smadja, G. Ferriol, S. Conseil, Y. Copin, Y. Gillard, W. Dusini, S. Jahnke, K. Prieto, E. Auricchio, N. Balbi, E. Balestra, A. Battaglia, P. Capobianco, V Chary, R. Corcione, L. Cogato, F. Delucchi, G. Franceschi, E. Gabarra, L. Gianotti, F. Grupp, F. Lentini, E. Ligori, S. Medinaceli, E. Morgante, G. Paterson, K. Romelli, E. Sauniere, L. Schirmer, M. Sirignano, C. Testera, G. Trifoglio, M. Troja, A. Valenziano, L. Frailis, M. Scodeggio, M. Barriere, J-C Berthe, M. Bodendorf, C. Caillat, A. Carle, M. Casas, R. Cho, H. Costille, A. Ducret, F. Garilli, B. Holmes, W. Hormuth, F. Hornstrup, A. Jhabvala, M. Kohley, R. Le Mignant, D. Lilje, P. B. Lloro, I Padilla, C. Polenta, G. Salvignol, J-C Seidel, G. Serra, B. Secroun, A. Stanco, L. Toledo-Moreo, R. Anselmi, S. Borsato, E. Caillat, L. Colodro-Conde, C. Conforti, V Davies, J. E. Renzi, A. Dal Corso, F. Davini, S. Derosa, A. Diaz, J. J. Di Domizio, S. Di Ferdinando, D. Farinelli, R. Ferrari, A. G. Fornari, F. Giacomini, F. Krause, O. Laudisio, F. Macias-Perez, J. Marpaud, J. Mauri, N. da Silva, R. Niclas, M. Passalacqua, F. Risso, I Lagier, P. Sorensen, A. N. Stassi, P. Steinwagner, J. Tenti, M. Thizy, C. Tosi, S. Travaglini, R. Tubio, O. Valieri, C. Ventura, S. Vescovi, C. Zoubian, J. Univ Claude Bernard Lyon 1 CNRS IN2P3 IP2I Lyon UMR 5822 F-69100 Villeurbanne France INFN Padova Via Marzolo 8 I-35131 Padua Italy Max Planck Inst Astron Konigstuhl 17 D-69117 Heidelberg Germany Aix Marseille Univ LAM CNES CNRS Marseille France INAF Osservatorio Astrofis & Sci Spazio Bologna Via Piero Gobetti 93-3 I-40129 Bologna Italy Aix Marseille Univ CPPM CNRS IN2P3 Marseille France Ist Nazl Fis Nucl Sez Genova Via Dodecaneso 33 I-16146 Genoa Italy INAF Osservatorio Astron Padova Via Osservatorio 5 I-35122 Padua Italy INAF Osservatorio Astrofis Torino Via Osservatorio 20 I-10025 Pino Torinese TO Italy CALTECH Infrared Proc & Anal Ctr Pasadena CA 91125 USA Univ Calif Los Angeles Los Angeles CA 90095 USA Alma Mater Studiorum Univ Bologna Dipartimento Fis & Astron Augusto Righi Via Piero Gobetti 93-2 I-40129 Bologna Italy Univ Genoa Dipartimento Fis Via Dodecaneso 33 I-16146 Genoa Italy Univ Oxford Dept Phys Keble Rd Oxford OX1 3RH England Max Planck Inst Extraterr Phys Giessenbachstr 1 D-85748 Garching Germany Ludwig Maximilians Univ Munchen Univ Sternwarte Munchen Fak Phys Scheinerstr 1 D-81679 Munich Germany INAF Osservatorio Astron Trieste Via GB Tiepolo 11 I-34143 Trieste Italy Univ Padua Dipartimento Fis & Astron G Galilei Via Marzolo 8 I-35131 Padua Italy INFN Bologna Via Irnerio 46 I-40126 Bologna Italy INAF IASF Milano Via Alfonso Corti 12 I-20133 Milan Italy CEA Saclay DRF IRFU Dept Ingn Syst Bat472 F-91191 Gif Sur Yvette France Univ Paris Saclay Univ Paris Cite AIM CNRSCEA F-91191 Gif Sur Yvette France Inst Estudis Espacials Catalunya IEEC Edifici RDITCampus UPC Barcelona 08860 Spain CSIC Inst Space Sci ICE Campus UABCarrer Can Magrans S-N Barcelona 08193 Spain CALTECH Jet Prop Lab 4800 Oak Grove Dr Pasadena CA 91109 USA Felix Hormuth Engn Goethestr 17 D-69181 Leimen Germany Tech Univ Denmark Elektrovej 327 DK-2800 Lyngby Denmark Cosm Dawn Ctr DAWN Copenhagen Denmark NASA Goddard Space Flight Ctr

ISBN: (纸本)9781510675308;9781510675292

Large-format infrared detectors are at the heart of major ground and space-based astronomical instruments, and the HgCdTe HxRG is the most widely used. The Near Infrared Spectrometer and Photometer (NISP) of the ESA's Euclid mission launched in July 2023 hosts 16 H2RG detectors in the focal plane. Their performance relies heavily on the effect of image persistence, which results in residual images that can remain in the detector for a long time contaminating any subsequent observations. Deriving a precise model of image persistence is challenging due to the sensitivity of this effect to observation history going back hours or even days. Nevertheless, persistence removal is a critical part of image processing because it limits the accuracy of the derived cosmological parameters. We will present the empirical model of image persistence derived from ground characterization data, adapted to the Euclid observation sequence and compared with the data obtained during the in-orbit calibrations of the satellite.

关键词： persistence HgCdTe H2RG near-infrared sensors Euclid NISP

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Euclid commissioning results: the Near Infrared Spectrometer and Photometer (NISP) signal detection chain

Euclid commissioning results: the Near Infrared Spectrometer...

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conference on space Telescopes and Instrumentation - Optical, Infrared, and Millimeter Wave

作者： Cogato, F. Medinaceli, E. Barbier, R. Dusini, S. Gillard, W. Jahnke, K. Prieto, E. Auricchio, N. Balbi, E. Balestra, A. Battaglia, P. Bonino, D. Capobianco, V Chary, R. Conseil, S. Corcione, L. Delucchi, G. Farinelli, R. Ferriol, S. Franceschi, E. Gabarra, L. Gianotti, F. Grupp, F. Lentini, E. Ligori, S. Morgante, G. Paterson, K. Romelli, E. Sauniere, L. Schirmer, M. Sirignano, C. Sirri, G. Testera, G. Trifoglio, M. Troja, A. Valenziano, L. Copin, Y. Frailis, M. Kubik, B. Scodeggio, M. Barriere, J-C Berthe, M. Bodendorf, C. Caillat, A. Carle, M. Casas, R. Cho, H. Costille, A. Ducret, F. Garilli, B. Holmes, W. Hormuth, F. Hornstrup, A. Jhabvala, M. Kohley, R. Le Mignant, D. Lilje, P. B. Lloro, I Padilla, C. Polenta, G. Salvignol, J-C Seidel, G. Serra, B. Secroun, A. Smadja, G. Stanco, L. Strada, P. Toledo-Moreo, R. Anselmi, S. Borsato, E. Caillat, L. Colodro-Conde, C. Conforti, V Davies, J. E. Renzi, A. Dal Corso, F. Davini, S. Derosa, A. Diaz, J. J. Di Domizio, S. Di Ferdinando, D. Ferrari, G. Fornari, F. Giacomini, F. Krause, O. Laudisio, F. Macias-Perez, J. Marpaud, J. Mauri, N. da Silva, R. Niclas, M. Passalacqua, F. Risso, I Lagier, P. Sorensen, A. N. Stassi, P. Steinwagner, J. Tenti, M. Thizy, C. Tosi, S. Travaglini, R. Tubio, O. Valieri, C. Ventura, S. Vescovi, C. Zoubian, J. Alma Mater Studiorum Univ Bologna Dipartimento Fis & Astron Augusto Righi Via Piero Gobetti 93-2 I-40129 Bologna Italy INAF Osservatorio Astrofis & Sci Spazio Bologna Via Piero Gobetti 93-3 I-40129 Bologna Italy Univ Claude Bernard Lyon 1 IP2I Lyon CNRS IN2P3 UMR 5822 F-69100 Villeurbanne France INFN Padova Via Marzolo 8 I-35131 Padua Italy Aix Marseille Univ CPPM CNRS IN2P3 Marseille France Max Planck Inst Astron Konigstuhl 17 D-69117 Heidelberg Germany Aix Marseille Univ CNES CNRS LAM Marseille France Ist Nazl Fis Nucl Sez Genova Via Dodecaneso 33 I-16146 Genoa Italy INAF Osservatorio Astron Padova Via Osservatorio 5 I-35122 Padua Italy INAF Osservatorio Astrofis Torino Via Osservatorio 20 I-10025 Pino Torinese TO Italy CALTECH Infrared Proc & Anal Ctr Pasadena CA 91125 USA Univ Calif Los Angeles Los Angeles CA 90095 USA Univ Genoa Dipartimento Fis Via Dodecaneso 33 I-16146 Genoa Italy Univ Oxford Dept Phys Keble Rd Oxford OX1 3RH England Max Planck Inst Extraterr Phys Giessenbachstr 1 D-85748 Garching Germany Ludwig Maximilians Univ Munchen Univ Sternwarte Munchen Fak Phys Scheinerstr 1 D-81679 Munich Germany INAF Osservatorio Astron Trieste Via GB Tiepolo 11 I-34143 Trieste Italy Univ Padua Dipartimento Fis & Astron G Galilei Via Marzolo 8 I-35131 Padua Italy INFN Bologna Via Irnerio 46 I-40126 Bologna Italy INAF IASF Milano Via Alfonso Corti 12 I-20133 Milan Italy CEA Saclay DRF IRFU Dept Ingn Syst Bat472 F-91191 Gif Sur Yvette France Univ Paris Saclay Univ Paris Cite AIM CNRSCEA F-91191 Gif Sur Yvette France Inst Estudis Espacials Catalunya IEEC Edifici RDITCampus Upc Barcelona 08860 Spain CSIC Inst Space Sci ICE Campus UABCarrer Can Magrans S-N Barcelona 08193 Spain CALTECH Jet Prop Lab 4800 Oak Grove Dr Pasadena CA 91109 USA Felix Hormuth Engn Goethestr 17 D-69181 Leimen Germany Tech Univ Denmark Elektrovej 327 DK-2800 Lyngby Denmark Cosm Dawn Ctr DAWN Copenhagen Denmark NASA Goddard Space Flight Ctr

ISBN: (纸本)9781510675087;9781510675070

Euclid, the M2 mission of the ESA's Cosmic Vision 2015-2025 program, aims to explore the Dark Universe by conducting a survey of approximately 14 000 deg(2) and creating a 3D map of the observable Universe of around 1.5 billion galaxies up to redshift z similar to 2. This mission uses two main cosmological probes: weak gravitational lensing and galaxy clustering, leveraging the high-resolution imaging capabilities of the Visual Imaging (VIS) instrument and the photometric and spectroscopic measurements of the Near Infrared Spectrometer and Photometer (NISP) instrument. This paper details some of the activities performed during the commissioning phase of the NISP instrument, following the launch of Euclid on July 1, 2023. In particular, we focus on the calibration of the NISP detectors' baseline and on the performance of a parameter provided by the onboard data processing (called NISP Quality Factor, QF) in detecting the variability of the flux of cosmic rays hitting the NISP detectors. The NISP focal plane hosts sixteen Teledyne HAWAII-2RG (H2RG) detectors. The calibration of these detectors includes the baseline optimization, which optimizes the dynamic range and stability of the signal acquisition. Additionally, this paper investigates the impact of Solar proton flux on the NISP QF, particularly during periods of high Solar activity. Applying a selection criterion on the QF (called NISP QF Proxy), the excess counts are used to monitor the amount of charged particles hitting the NISP detectors. A good correlation was found between the Solar proton flux component above 30 MeV and the NISP QF Proxy, revealing that NISP detectors are not subject to the lower energy components, which are absorbed by the shielding provided by the spacecraft.

关键词： Euclid NISP Quality Factor Near-Infrared Detectors H2RG Cosmic Rays

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Enhanced YOLOv7 Model for Accurate Vehicle Detection from UAV Imagery

Enhanced YOLOv7 Model for Accurate Vehicle Detection from UA...

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Intelligent Innovations in Engineering and Technology (ICIIET), International conference on

作者： Sangeeth Mathew John Fathima Abdul Kareem Sachin Gee Paul Abdul Gafur M Saeed Al Mansoori Alavikunhu Panthakkan Ilahia College of Engineering and Technology Kerala India Mohammed Bin Rashid Space Centre (MBRSC) Dubai United Arab Emirates College of Engineering and IT University of Dubai Dubai United Arab Emirates

The advancements in unmanned aerial vehicle (UAV) technology have revolutionized aerial surveillance and monitoring applications, with vehicle detection being a crucial aspect in fields like traffic management, urban planning, and security. However, traditional vehicle detection methods face challenges in handling complex scenarios, real-time processing, and scalability. To overcome these challenges, this research paper proposes an advanced AI-driven vehicle detection system utilizing the YOLOv7 model. The YOLOv7 model, a cutting-edge object detection algorithm, excels in real-time processing and precise object localization in images and video frames. This study harnesses the capabilities of YOLOv7 for vehicle detection from UAV imagery. By integrating the YOLOv7 model with UAV data, the proposed system achieves robust and efficient vehicle detection in diverse environmental conditions. Extensive experimental evaluations are conducted on a real-world UAV imagery dataset to assess the performance of the proposed system. The evaluations involve comparing the proposed AI-driven vehicle detection system with existing methods in terms of accuracy, processing speed, and scalability. The results demonstrate the superior performance of the YOLOv7 based system, achieving high detection rates with minimal computational overhead. The findings of this research significantly contribute to the field of vehicle detection from UAV imagery by introducing an advanced AI driven approach utilizing the YOLOv7 model. The proposed system has the potential to enhance various applications, including traffic monitoring, accident prevention, and urban planning. Furthermore, this study provides valuable insights into the integration of deep learning algorithms with UAV technology, paving the way for future advancements in aerial surveillance and monitoring systems.

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Standing Still Is Not an Option: Alternative Baselines for Attainable Utility Preservation 1

引用

Machine Learning and Knowledge Extraction 7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain conference, CD-MAKE 2023

作者： Eresheim, Sebastian Kovac, Fabian Adrowitzer, Alexander Research Group Security and Privacy University of Vienna Vienna Austria Data Intelligence Research Group St. Pölten University of Applied Sciences St. Pölten Austria

ISBN: (数字)9783031408373

ISBN: (纸本)9783031408366

Specifying reward functions without causing side effects is still a challenge to be solved in Reinforcement Learning. Attainable Utility Preservation (AUP) seems promising to preserve the ability to optimize for a correct reward function in order to minimize negative side-effects. Current approaches however assume the existence of a no-op action in the environment’s action space, which limits AUP to solve tasks where doing nothing for a single time-step is a valuable option. Depending on the environment, this cannot always be guaranteed. We introduce four different baselines that do not build on such actions and therefore extend the concept of AUP to a broader class of environments. We evaluate all introduced variants on different AI safety gridworlds and show that this approach generalizes AUP to a broader range of tasks, with only little performance losses. © 2023, IFIP International Federation for Information processing.

关键词： Reinforcement learning

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