FOUNDATIONS FOR CONTINUOUS ENGINEERING OF TRUSTWORTHY AUTONOMY

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Report: Systematic and coverage-driven testing of learning components

Report Systematic and coveragedriven testing of learning components ULIV

Report: Formal verification of learning components

Report Formal verification of learning components ULIV

Report: Provable safe reinforcement learning

Report Provable safe reinforcement learning TUG

Formal specification for learning-enabled autonomous systems

Formal specification for learningenabled autonomous systems BIU

Report: AI-enabled systematic and intelligent testing of autonomous systems

Report AIenabled systematic and intelligent testing of autonomous systems BIU

Report: Early validation result WP4

Report Early validation result WP4 TUG

"Report on workshop #1 organisation"

Report on workshop 1 organisation UGA

Report: Understanding decision faithfulness of machine learning components

Report Understanding decision faithfulness of machine learning components DNDE

Report: Early validation result WP3

Report Early validation result WP3 FORTISS

"Report on workshop #2 organisation"

Report on workshop 2 organisation UGA

Report: Runtime enforcement for performance while guaranteeing safety

Report Runtime enforcement for performance while guaranteeing safety TUG

Dissemination Action Plan including project corporate identity

Dissemination Action Plan including project corporate identity UGA

Report on public demonstration

Report on public demonstration SIEMENS

Standardisation final report

Standardisation final report INTEL

Dissemination Action Plan including project corporate identity update

Dissemination Action Plan including project corporate identity update UGA

Report: Systematic refinement

Report Systematic refinement BIU

Dissemination set (poster, leaflet, Kakemono) and Website

Dissemination set poster leaflet Kakemono and Website UGA

Project mini-video

Project minivideo UGA

Tool and manual: integrated evidential tool chain for the incremental and continuous generation of safety & security assurance cases

Tool and manual: integrated evidential tool chain for the incremental and continuous generation of safety & security assurance cases (FORTISS)

Project newsletter 1

Project newsletter 1 LUP

Project newsletter 2

Project newsletter 2 (L-UP°

Tool + Manual: Agent building toolkit for performance with safety

Tool + Manual: Agent building toolkit for performance with safety (TUG)

Tool + Manual: Verification and testing of learning-enabled systems

Tool + Manual: Verification and testing of learning-enabled systems (FORTISS)

Project newsletter 3

Project newsletter 3 (L-UP)

Tool + manual: modelling and simulation of autonomy

Tool + manual: modelling and simulation of autonomy (AUTh)

Pubblicazioni

Online Shielding for Reinforcement Learning

Autori: Bettina Könighofer; Julian Rudolf; Alexander Palmisano; Martin Tappler; Roderick Bloem
Pubblicato in: Innovations in Systems and Software Engineering, 2022, ISSN 1614-5046
Editore: Springer Verlag
DOI: 10.48550/arxiv.2212.01861

Survey on mining signal temporal logic specifications

Autori: Ezio Bartocci; Cristinel Mateis; Eleonora Nesterini; Dejan Nickovic
Pubblicato in: Information and Computation journal, Numero 08905401, 2022, ISSN 0890-5401
Editore: Academic Press
DOI: 10.1016/j.ic.2022.104957

Embedding and Extraction of Knowledge in Tree Ensemble Classifiers

Autori: Xingyu Zhao, Xiaowei Huang
Pubblicato in: Machine Learning journal, 2021, ISSN 1573-0565
Editore: Springer
DOI: 10.1007/s10994-021-06068-6

Hierarchical Distribution-Aware Testing of Deep Learning

Autori: Wei Huang, Xingyu Zhao, ALEC BANKS, VICTORIA COX, Xiaowei Huang
Pubblicato in: Journal ACM transactions on Software Engineering Methods, 2023, ISSN 1049-331X
Editore: Association for Computing Machinary, Inc.
DOI: 10.48550/arxiv.2205.08589

Semantic Modeling and Analysis of Natural Language System Requirements

Autori: Konstantinos Mokos, Theodoros Nestoridis, Panagiotis Katsaros, Nick Bassiliades
Pubblicato in: IEEE Access Journal, Numero 21693536, 2022, Pagina/e 84094-84119, ISSN 2169-3536
Editore: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/access.2022.3197281

Mining Hyperproperties using Temporal Logic

Autori: Ezio Bartocci, Cristinel Mateis, Eleonora Nesterini, Nickovic, Dejan
Pubblicato in: ACM Transactions on Embedded Computing Systems, Numero Volume 22, Numero 5, Article No. 156, 2023, Pagina/e pp 1–26, ISSN 1539-9087
Editore: Association for Computing Machinary, Inc.
DOI: 10.1145/3609394

Coverage-Guided Testing for Recurrent Neural Networks

Autori: Wei Huang, Youcheng Sun, Xingyu Zhao, James Sharp, Wenjie Ruan, Jie Meng, Xiaowei Huang
Pubblicato in: IEEE Transactions on Reliability, 2021, Pagina/e 1-16, ISSN 0018-9529
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tr.2021.3080664

Reflections on Surrogate-Assisted Search-Based Testing: A Taxonomy and Two Replication Studies based on Industrial ADAS and Simulink Models

Autori: Shiva Nejati, Lev Sorokin, Damir Safin, Federico Formica, Mohammad Mahdi Mahboob, Claudio Menghi
Pubblicato in: Information and Software Technology Journal, 2023, Pagina/e 107286, ISSN 0950-5849
Editore: Elsevier BV
DOI: 10.1016/j.infsof.2023.107286

The Unnecessity of Assuming Statistically Independent Tests in Bayesian Software Reliability Assessments

Autori: Kizito Salako; Xingyu Zhao
Pubblicato in: IEEE Transactions on Software Engineering, Numero 6, 2023, Pagina/e 2829 - 2838, ISSN 0098-5589
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.48550/arxiv.2208.00462

Analyzing Intentional Behavior in Autonomous Agents Under Uncertainty

Autori: Filip Cano Córdoba, Samuel Judson, Timos Antonopoulos, Katrine Bjorner, Nicholas Shoemaker, Scott Shapiro, Ruzica Piskac, Bettina Könighofer
Pubblicato in: Proceedings of the IJCAI 2023 - 32nd International Joint Conference on Artificial Intelligence, 2023, Pagina/e 372--381, ISBN 978-1-956792-03-4
Editore: ijcai.org
DOI: 10.24963/ijcai.2023/42

How does Weight Correlation Affect the Generalisation Ability of Deep Neural Networks

Autori: Jin, Gaojie; Yi, Xinping; Zhang, Liang; Zhang, Lijun; Schewe, Sven; Huang, Xiaowei
Pubblicato in: 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Numero 1, 2020
Editore: Neural Information Processing Systems

Safe, Deterministic Trajectory Planning for Unstructured and Partially Occluded Environments

Autori: Sebastian vom Dorff, Maximilian Kneissl, Martin Franzle
Pubblicato in: 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021, Pagina/e 969-975, ISBN 978-1-7281-9142-3
Editore: IEEE
DOI: 10.1109/itsc48978.2021.9565022

Continuous Safety Verification of Neural Networks

Autori: Chih-Hong Cheng, Rongjie Yan
Pubblicato in: 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2021, Pagina/e 1478-1483, ISBN 978-3-9819263-5-4
Editore: IEEE
DOI: 10.23919/date51398.2021.9473994

Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications

Autori: Wenjie Ruan; Xinping Yi; Xiaowei Huang
Pubblicato in: CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Numero 2021 Proceeding, 2021, ISBN 978-1-4503-8446-9
Editore: ACM
DOI: 10.1145/3459637.3482029

Detecting Operational Adversarial Examples for Reliable Deep Learning

Autori: Zhao, Xingyu; Huang, Wei; Schewe, Sven; Dong, Yi; Huang, Xiaowei; IEEE,
Pubblicato in: 51ST ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS - SUPPLEMENTAL VOL (DSN 2021), Numero 1, 2021, ISBN 978-1-6654-3566-6
Editore: IEEE
DOI: 10.1109/dsn-s52858.2021.00013

Runtime Verification for FMI-Based Co-simulation

Autori: Anastasios Temperekidis, Nikolaos Kekatos, and Panagiotis Katsaros
Pubblicato in: Runtime Verification. RV 2022. Lecture Notes in Computer Science, vol 13498, 2022
Editore: Springer, Cham
DOI: 10.1007/978-3-031-17196-3_19

Enhancing Adversarial Training with Second-Order Statistics of Weights

Autori: Gaojie Jin, Xinping Yi, Liang Zhang, Lijun Zhang, Sven Schewe, Xiaowei Huang
Pubblicato in: CVPR 2022 - 2022 Conference on Computer Vision and Pattern Recognition, 2022
Editore: IEEE

Strategies for MDP Bisimilarity Equivalence and Inequivalence

Autori: Stefan Kiefer, Qiyi Tang
Pubblicato in: Concur 2022 - 33RD INTERNATIONAL CONFERENCE ON CONCURRENCY THEORY, 2022, Pagina/e 32:1--32:22, ISBN 978-3-95977-246-4
Editore: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
DOI: 10.4230/lipics.concur.2022.32

Learning from Demonstrations of Critical Driving Behaviours Using Driver’s Risk Field

Autori: Yurui Du, Flavia Sofia Acerbo, Jens Kober, Tong Duy Son
Pubblicato in: IFAC World Congress 2023, 2023
Editore: Elsevier ScienceDirect
DOI: 10.48550/arxiv.2210.01747

BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations

Autori: Xingyu Zhao, Xiaowei Huang, et. Al.
Pubblicato in: UAI2021 Proceedings of Machine Learning Research (PMLR), Numero Zhao, X.,Huang, W, Huang, X., Robu, V., and Flynn, D. (2021). BayLime: Bayesian local interpretable model-agnostic explanations. UAI2021., 2021
Editore: AAAI press

Hidden 1-Counter Markov Models and How to Learn Them

Autori: Mehmet Kurucan, Mete Ozbaltan, Sven Schewe, Dominik Wojtczak
Pubblicato in: IJCAI 2022 - 31st International Joint Conference on Artificial Intelligence, 2022, Pagina/e 4857-4863
Editore: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2022/673

Mining Specification Parameters for Multi-Class Classification

Autori: Ezio Bartocci, Cristinel Mateis, Eleonora Nesterini, and Dejan Nickovic
Pubblicato in: Proceedings of RV 2023 - 23rd International Conference, RV 2023, Thessaloniki, Greece, October 3–6, 2023, 2023, ISBN 978-3-031-44266-7
Editore: Springer Nature
DOI: 10.1007/978-3-031-44267-4

Reliable Multimodal Trajectory Prediction via Error Aligned Uncertainty Optimization

Autori: Neslihan Kose Cihangir, Ranganath Krishnan, Akash Dhamasia, Omesh Tickoo, Michael Paulitsch
Pubblicato in: SAIAD 2022 - 4th Workshop Safe Artificial Intelligence for Automated Driving, 2023
Editore: Springer
DOI: 10.48550/arxiv.2212.04812

Real-time Nonlinear MPC Strategy with Full Vehicle Validation for Autonomous Driving

Autori: Jean Pierre Allamaa, Petr Listov, Herman Van der Auweraer, Colin Jones, Tong Duy Son
Pubblicato in: American Control Conference (ACC) 2022, 2021
Editore: IEEE

Attribute Repair for Threat Prevention

Autori: Tarrach Thorsten; Ebrahimi Masoud; König Sandra; Schmittner Christoph; Bloem Roderick; Nickovic Dejan
Pubblicato in: SafeComp 2023 proceedings, 2023, ISBN 978-3-031-40922-6
Editore: Springer
DOI: 10.1007/978-3-031-40923-3

Safe Imitation Learning on Real-Life Highway Data for Human-like Autonomous Driving

Autori: Flavia Sofia Acerbo, Mohsen Alirezaei, Herman Van der Auweraer, Tong Duy Son.
Pubblicato in: 24th IEEE International Conference on Intelligent Transportation - ITSC2021, 2021
Editore: IEEE

Reinforcement Learning from Simulation to Real World Autonomous Driving using Digital Twin

Autori: Kevin L. Voogd, Jean-Pierre Allamaa, Javier Alonso-Mora, Son Tong
Pubblicato in: IFAC World Congress 2023, 2023
Editore: Elsevier ScienceDirect
DOI: 10.48550/arxiv.2211.14874

Safety Metrics for Semantic Segmentation in Autonomous Driving

Autori: Chih-Hong Cheng, Alois Knoll, Hsuan-Cheng Liao
Pubblicato in: 2021 IEEE International Conference on Artificial Intelligence Testing (AITest), 2021, Pagina/e 57-64, ISBN 978-1-6654-3481-2
Editore: IEEE
DOI: 10.1109/aitest52744.2021.00021

On Neural Network Equivalence Checking using SMT Solvers

Autori: Charis Eleftheriadis, Nikolaos Kekatos, Panagiotis Katsaros, and Stavros Tripakis
Pubblicato in: Formal Modeling and Analysis of Timed Systems. FORMATS 2022. Lecture Notes in Computer Science, 2022
Editore: Springer, Cham
DOI: 10.1007/978-3-031-15839-1_14

TEMPEST - Synthesis Tool for Reactive Systems and Shields in Probabilistic Environments

Autori: Stefan Pranger; Bettina Könighofer; Lukas Posch; Roderick Bloem
Pubblicato in: ATVA 2021, Numero 1, 2021, ISBN 978-3-030-88884-8
Editore: Springer
DOI: 10.1007/978-3-030-88885-5_15

Formal Specification for Learning-Enabled Autonomous Systems

Autori: Saddek Bensalem, Chih-Hong Cheng, Xiaowei Huang, Panagiotis Katsaros, Adam Molin, Dejan Nickovic, Doron Peled
Pubblicato in: Software Verification and Formal Methods for ML-Enabled Autonomous Systems, Numero [2022], 2022, Pagina/e p.131-143, ISBN 978-3-031-21221-5
Editore: Springer
DOI: 10.1007/978-3-031-21222-2_8

Large-Scale Application of Fault Injection into PyTorch Models -- an Extension to PyTorchFI for Validation Efficiency

Autori: Ralf Gräfe, Qutub Syed Sha, Florian Geissler, Michael Paulitsch
Pubblicato in: 2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S). Proceedings of DSN 2023 Industry track, 2023, Pagina/e 56 – 62, ISBN 979-8-3503-2545-4
Editore: IEEE
DOI: 10.1109/dsn-s58398.2023.00025

Simulation-based Safety Assurance for an AVP System incorporating Learning-Enabled Components

Autori: Hasan Esen, Brian Hsuan-Cheng Liao
Pubblicato in: 10th International Symposium on Development Methodology, 2023, ISBN 978-3-9816971-6-2
Editore: AVL Deutschland
DOI: 10.48550/arxiv.2311.03362

Monitoring Object Detection Abnormalities via Data-Label and Post-Algorithm Abstractions

Autori: Chen, Yuhang; Cheng, Chih-Hong; Yan, Jun; Yan, Rongjie
Pubblicato in: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021), 2021
Editore: IEEE

A Low-Cost Strategic Monitoring Approach for Scalable and Interpretable Error Detection in Deep Neural Networks

Autori: Florian Geissler, Syed Qutub, Michael Paulitsch, and Karthik Pattabiraman
Pubblicato in: SAFECOMP2023 - 42nd International Conference on Computer Safety, Reliability and Security, 2023, ISBN 978-3-031-40922-6
Editore: Springer
DOI: 10.1007/978-3-031-40923-3_7

Provably-Robust Runtime Monitoring of Neuron Activation Patterns

Autori: Chih-Hong Cheng
Pubblicato in: 2021 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2021, Pagina/e 1310-1313, ISBN 978-3-9819263-5-4
Editore: IEEE
DOI: 10.23919/date51398.2021.9473957

Safety and reliability of deep learning - (brief overview)

Autori: Xiaowei Huang
Pubblicato in: Proceedings of the 1st International Workshop on Verification of Autonomous & Robotic Systems, 2021, Pagina/e 1-2, ISBN 9781450384445
Editore: ACM
DOI: 10.1145/3459086.3459636

Model-Free Reinforcement Learning for Lexicographic ω-Regular Objectives

Autori: Ernst Moritz Hahn, Mateo Perez, Sven Schewe, Fabio Somenzi, Ashutosh Trivedi, and Dominik Wojtczak
Pubblicato in: 24th International Symposium, FM 2021, 2021, ISBN 978-3-030-90870-6
Editore: Springer, Cham
DOI: 10.1007/978-3-030-90870-6_8

Structural Coding: A Low-Cost Scheme to Protect CNNs from Large-Granularity Memory Faults

Autori: Ali Asgari Khoshouyeh, Florian Geissler, Seyed Qutub, Michael Paulitsch, Prashant Nair, Karthik Pattabiraman
Pubblicato in: SC 23 - The International Conference for High Performance Computing, Networking, Storage, and Analysis, 2023, ISBN 979-8-4007-0109-2
Editore: ACM Association for Computing Machinery, New York, NY, United States
DOI: 10.1145/3581784.3607084

Testing Autonomous Systems with Believed Equivalence Refinement

Autori: Chih-Hong Cheng, Rongjie Yan
Pubblicato in: 2021 IEEE International Conference on Artificial Intelligence Testing (AITest), 2021, Pagina/e 49-56, ISBN 978-1-6654-3481-2
Editore: IEEE
DOI: 10.1109/aitest52744.2021.00020

Assessing the reliability of deep learning classifiers through robustness evaluation and operational profiles

Autori: Zhao, X., Huang, W., Banks, A., Cox, V., Flynn, D., Schewe, S., and Huang, X.
Pubblicato in: AISafety’21 Workshop at IJCAI’21, 2021
Editore: CEUR

Information-flow Interfaces

Autori: Ezio Bartocci, Thomas Ferrère, Thomas A. Henzinger, Dejan Nickovic & Ana Oliveira da Costa
Pubblicato in: Fundamental Approaches to Software Engineering. FASE 2022. Lecture Notes in Computer Science, vol 13241., 2022, ISBN 978-3-030-99428-0
Editore: Springer, Cham
DOI: 10.1007/978-3-030-99429-7_1

Formal XAI via Syntax-Guided Synthesis

Autori: Bjørner, Katrine; Judson, Samuel; Cano, Filip; Goldman, Drew; Shoemaker, Nick; Piskac, Ruzica; Könighofer, Bettina
Pubblicato in: AISoLA 2023 proceedings, 2023, ISBN 978-3-031-46002-9
Editore: Springer Cham
DOI: 10.5281/zenodo.8382832

Search-Based Testing of Reinforcement Learning

Autori: Martin Tappler, Filip Cano Cordoba, Bernhard Aichernig, Bettina Könighofer
Pubblicato in: Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI 2022) Main Track., Numero Thirty-First Conference, 23-29 July 2022, 2022, Pagina/e 503-510, ISBN 978-1-956792-00-3
Editore: ijcai.org
DOI: 10.24963/ijcai.2022/72

A Hierarchical HAZOP-Like Safety Analysis for Learning-Enable Systems

Autori: Yi Qi, Philippa Ryan, Wei Huang, Xingyu Zhao and Xiaowei Huang
Pubblicato in: AISafety 2022 workshop at IJCAI2022, 2022
Editore: CEUR Workshop Proceedings
DOI: 10.48550/arxiv.2206.10216

Safety Shielding under Delayed Observation

Autori: Filip Cano, Alexander Palmisano, Martin Fraenzle, Roderick Bloem and Bettina Koenighofer
Pubblicato in: ICAPS 2023 - 33rd International Conference on Automated Planning and Scheduling, 2023, ISSN 2334-0843
Editore: AAAI Press.
DOI: 10.1609/icaps.v33i1.27181

Provable Correct and Adaptive Simplex Architecture for Bounded-Liveness Properties

Autori: Maderbacher, B., Schupp, S., Bartocci, E., Bloem, R., Ničković, D. and Könighofer, B.
Pubblicato in: SPIN'23 proceedings, 2023, ISBN 978-3-031-32157-3
Editore: Springer Cham
DOI: 10.1007/978-3-031-32157-3_8

Specification-guided critical scenario identification for automated driving

Autori: Adam Molin, Edgar A. Aguilar, Dejan Nickovic, Mengjia Zhu, Alberto Bemporad, and Hasan Esen
Pubblicato in: FM 2023 - 25th International Symposium on Formal Methods, 2023, Pagina/e 610-621, ISBN 978-3-031-27480-0
Editore: Springer
DOI: 10.1007/978-3-031-27481-7_35

Towards a Digital Twin Architecture with Formal Analysis Capabilities for Learning-Enabled Autonomous Systems

Autori: Anastasios Temperekidis, Nikolaos Kekatos, Panagiotis Katsaros, Weicheng He, Saddek Bensalem, Hisham AbdElSabour, Mohamed AbdElsalam, Ashraf Salem
Pubblicato in: MESAS 2022 - 9th International Conference on Modelling and Simulation for Autonomous Systems, Numero 2022 Proceedings, 2023, Pagina/e 163-181
Editore: Springer Cham
DOI: 10.1007/978-3-031-31268-7_10

Hardware Faults that Matter: Understanding and Estimating the Safety Impact of Hardware Faults on Object Detection DNNs

Autori: Syed Qutub, Florian Geissler, Yang Peng, Ralf Gräfe, Michael Paulitsch, Gereon Hinz, and Alois Knoll
Pubblicato in: Safecomp 2022, Numero 41st, 2022, Pagina/e 298-318, ISBN 978-3-031-14835-4
Editore: Springer
DOI: 10.1007/978-3-031-14835-4_20

DeepSTL - From English Requirements to Signal Temporal Logic

Autori: Jie He, Ezio Bartocci, Dejan Nickovic and Radu Grosu
Pubblicato in: ICSE '22: Proceedings of the 44th International Conference on Software Engineering, 2022, Pagina/e 610–622
Editore: ACM Digital Library
DOI: 10.1145/3510003.3510171

Mining Shape Expressions with ShapeIt

Autori: Ezio Bartocci, Jyotirmoy Deshmukh, Cristinel Mateis, Eleonora Nesterini, Dejan Nickovic, and Xin Qin
Pubblicato in: 19th International Conference on Software Engineering and Formal Methods (SEFM'21), 2021
Editore: Springer
DOI: 10.5281/zenodo.5597000

Sampling of Shape Expressions with ShapEx

Autori: Nicolas Basset; Thao Dang; Felix Gigler; Cristinel Mateis; Dejan Nickovic
Pubblicato in: ACM Digital Library, 2021
Editore: ACM
DOI: 10.5281/zenodo.5550069

EPMC Gets Knowledge in Multi-Agent Systems

Autori: Chen Fu, Ernst Moritz Hahn, Yong Li, Sven Schewe, Meng Sun, Andrea Turrini, and Lijun Zhang
Pubblicato in: VMCAI 2022 - 23rd International Conference on Verification, Model Checking, and Abstract Interpretation, Numero volume 13182, 2022, Pagina/e pages: 93-107, ISBN 978-3-030-94583-1
Editore: Springer
DOI: 10.1007/978-3-030-94583-1_5

Are Transformers More Robust? Towards Exact Robustness Verification for Transformers

Autori: Hsuan-Cheng Liao, Chih-Hong Cheng, Hasan Esen, Alois Knoll
Pubblicato in: SafeComp 2023 proceedings, Numero vol 14181, 2023, ISBN 978-3-031-40922-6
Editore: Springer, Cham
DOI: 10.1007/978-3-031-40923-3_8

Automata Learning meets Shielding

Autori: Martin Tappler, Stefan Pranger, Bettina K¨onighofer, Edi Muˇskardin, Roderick Bloem, and Kim Larsen
Pubblicato in: ISoLA 2022 - 11th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation Principles, 2022, Pagina/e pp 335–359
Editore: Springer
DOI: 10.48550/arxiv.2212.01838

Robustness Verification for Attention Networks using Mixed Integer Programming

Autori: Hsuan-Cheng Liao, Chih-Hong Cheng, Maximilian Kneissl, Alois Knoll
Pubblicato in: 2022
Editore: Arxiv
DOI: 10.48550/arxiv.2202.03932

OpenSBT: A Modular Framework for Search-based Testing of Automated Driving Systems

Autori: Lev Sorokin, Tiziano Munaro, Damir Safin, Brian Hsuan-Cheng Liao, Adam Molin
Pubblicato in: Arxiv, 2023
Editore: Arxiv
DOI: 10.48550/arxiv.2306.10296

Virtual Reality Assisted Human Perception in ADAS Development: a Munich 3D Model Study

Autori: Felix Bognar, Oster Markus, Herman Van der Auweraer, Tong Duy Son
Pubblicato in: 2022
Editore: Arxiv
DOI: 10.48550/arxiv.2208.07208

Adversarial Robustness Improvement for Deep Neural Networks

Autori: Charis Eleftheriadis, Andreas Symeonidis, and Panagiotis Katsaros
Pubblicato in: Preprint accepted with revision in Machine Vision and Applications, 2023
Editore: Springer
DOI: 10.21203/rs.3.rs-3351648/v1

Improving the Safety of 3D Object Detectors in Autonomous Driving using IoGT and Distance Measures

Autori: Hsuan-Cheng Liao, Chih-Hong Cheng, Hasan Esen, Alois Knoll
Pubblicato in: 2023
Editore: Arxiv
DOI: 10.48550/arxiv.2209.10368

Towards Trustworthy Camera-Based Sensing and Perception Systems

Autori: Christian Berghoff, Jona Böddinghaus, Vasilios Danos, Gabrielle Davelaar, Thomas Doms, Heiko Ehrich, Alexandru Forrai, Radu Grosu, Ronan Hamon, Henrik Junklewitz, Matthias Neu, Simon Romanski, Wojciech Samek, Dirk Schlesinger, Jan-Eve Stavesand, Sebastian Steinbach, Arndt von Twickel, Robert Walter, Johannes Weissenböck, Markus Wenzel, Thomas Wiegand
Pubblicato in: Whitepaper | May 2022. Towards Auditable AI Systems. From Principles to Practice. Based on the 2nd international Workshop “Towards Auditable AI Systems”, October 26th 2021, Fraunhofer Forum Digitale Technologien, Berlin, organized by the Federal Office for Information Security Germany, the TÜV-Verband and the Fraunhofer HHI, 2022
Editore: Bundesamt für Sicherheit in der Informationstechnik, Fraunhofer-Institut für Nachrichtentechnik, TÜV-Verband e. V.

Dependability Analysis of Deep Reinforcement Learning based Robotics and Autonomous Systems

Autori: Dong, Yi; Zhao, Xingyu; Huang, Xiaowei
Pubblicato in: Numero 2, 2021
Editore: ArXiv
DOI: 10.48550/arxiv.2109.06523

A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation

Autori: Xiaowei Huang, Wenjie Ruan, Wei Huang, Gaojie Jin, Yi Dong, Changshun Wu, Saddek Bensalem, Ronghui Mu, Yi Qi, Xingyu Zhao, Kaiwen Cai, Yanghao Zhang, Sihao Wu, Peipei Xu, Dengyu Wu, Andre Freitas, Mustafa A. Mustafa
Pubblicato in: 2023
Editore: Arxiv
DOI: 10.48550/arxiv.2305.11391

Deciding What is Good-for-MDPs

Autori: Sven Schewe, Qiyi Tang and Tansholpan Zhanabekova
Pubblicato in: 2022
Editore: Arxiv
DOI: 10.48550/arxiv.2202.07629

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