@inproceedings{Badings2024TACAS,

title = {CTMCs with Imprecisely Timed Observations},

author = {Thom S. Badings and Matthias Volk and Sebastian Junges and Mariëlle Stoelinga and Nils Jansen},

url = {https://doi.org/10.48550/arXiv.2401.06574},

doi = {10.48550/ARXIV.2401.06574},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {TACAS 2024},

keywords = {Model checking, Robustness},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/fmics/SoltaniVDLS23,

title = {Optimal Spare Management via Statistical Model Checking: A Case  Study in Research Reactors},

author = {Reza Soltani and Matthias Volk and Leonardo Diamonte and Milan Lopuhaä-Zwakenberg and Mariëlle Stoelinga},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {FMICS},

volume = {14290},

pages = {205–223},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Maintenance optimization, Spare part management},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{marinho2023comparison,

title = {A Comparison of Optical Sensing Systems with Piezo-Electric Sensors for Impact Identification of Composite Plates},

author = {Natália Ribeiro Marinho and Richard Loendersloot and Tiedo Tinga and Frank Grooteman and Jan Willem Wiegman},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {14th International Workshop on Structural Health Monitoring, IWSHM 2023},

pages = {1127–1133},

organization = {DEStech Publications, Inc},

keywords = {Sensors},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ESREL_SAFEST,

title = {SAFEST: the static and dynamic fault tree analysis tool},

author = {Matthias Volk and Muzammil Ibne Irshad and Joost-Pieter Katoen and Falak Sher and Mariëlle Stoelinga and Ahmad Zafar},

url = {https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Frpsonline.com.sg%2Fproceedings%2Fesrel2023%2Fpdf%2FP407.pdf&data=05%7C01%7Cthom.badings%40ru.nl%7Ca990329295674cee5f5d08dbaf7827ca%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C638296704861847798%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=k10g3PYGpeP4WuH6RDn7YMsiqhlk5B1FHiDTxEFBNn4%3D&reserved=0},

doi = {10.3850/978-981-18-8071-1_P407-cd},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {ESREL},

pages = {193–200},

publisher = {Research Publishing},

keywords = {Fault tree analysis},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ESREL_PID,

title = {From Fault Trees to Piping and Instrumentation Diagrams},

author = {Wouter Bos and Matthias Volk and Mariëlle Stoelinga and Marc Bouissou and Pavel Krčál},

url = {https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Frpsonline.com.sg%2Fproceedings%2Fesrel2023%2Fpdf%2FP537.pdf&data=05%7C01%7Cthom.badings%40ru.nl%7Ca990329295674cee5f5d08dbaf7827ca%7C084578d9400d4a5aa7c7e76ca47af400%7C1%7C0%7C638296704861847798%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=Hidiz%2FP6txOBvRII081VFhAlkz0yN%2BfCg2wehIpTbK0%3D&reserved=0},

doi = {10.3850/978-981-18-8071-1_P537-cd},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {ESREL},

pages = {1234–1235},

publisher = {Research Publishing},

keywords = {Fault tree analysis},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/cav/BadingsJMTJ23,

title = {Efficient Sensitivity Analysis for Parametric Robust Markov Chains},

author = {Thom S. Badings and Sebastian Junges and Ahmadreza Marandi and Ufuk Topcu and Nils Jansen},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {CAV (3)},

volume = {13966},

pages = {62–85},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Decision-making under uncertainty, Model learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Castellini2023,

title = {Scalable Safe Policy Improvement via Monte Carlo Tree Search},

author = {Alberto Castellini and Federico Bianchi and Edoardo Zorzi and Thiago D. Simão and Alessandro Farinelli and Matthijs T. J. Spaan},

url = {https://proceedings.mlr.press/v202/castellini23a.html},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {ICML},

pages = {3732–3756},

keywords = {Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Gross2023targeted,

title = {Targeted Adversarial Attacks on Deep Reinforcement Learning Policies via Model Checking},

author = {Dennis Gross and Thiago D. Simão and Nils Jansen and Guillermo A. Pérez},

url = {https://www.scitepress.org/PublicationsDetail.aspx?ID=KWi7kyMXAok=},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {ICAART},

pages = {501–508},

keywords = {Machine learning, Model checking},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Koops2023recursive,

title = {Recursive Small-Step Multi-Agent A* for Dec-POMDPs},

author = {Wietze Koops and Nils Jansen and Sebastian Junges and Thiago D. Simão},

url = {https://www.ijcai.org/proceedings/2023/600},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {IJCAI},

pages = {5402–5410},

keywords = {Decision-making under uncertainty},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Wienhoft2023more,

title = {More for Less: Safe Policy Improvement with Stronger Performance Guarantees},

author = {Patrick Wienhöft and Marnix Suilen and Thiago D. Simão and Clemens Dubslaff and Christel Baier and Nils Jansen},

url = {https://www.ijcai.org/proceedings/2023/490},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {IJCAI},

pages = {4406–4415},

keywords = {Decision-making under uncertainty, Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Yang2023reinforcement,

title = {Reinforcement Learning by Guided Safe Exploration},

author = {Qisong Yang and Thiago D. Simão and Nils Jansen and Simon H. Tindemans and Matthijs T. J. Spaan},

url = {https://arxiv.org/abs/2307.14316},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {ECAI},

keywords = {Decision-making under uncertainty, Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Rickard2023QEST,

title = {Formal Controller Synthesis for Markov Jump Linear Systems with Uncertain  Dynamics},

author = {Luke Rickard and Thom S. Badings and Licio Romao and Nils Jansen and Alessandro Abate},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {QEST},

keywords = {Decision-making under uncertainty, Robustness},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Koprulu2023,

title = {Risk-aware Curriculum Generation for Heavy-tailed Task Distributions},

author = {Cevahir Koprulu and Thiago D. Simão and Nils Jansen and Ufuk Topcu},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {UAI},

pages = {1132–1142},

keywords = {Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Krale2023act,

title = {Act-Then-Measure: Reinforcement Learning for Partially Observable Environments with Active Measuring},

author = {Merlijn Krale and Thiago D. Simão and Nils Jansen},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {ICAPS},

pages = {212-220},

keywords = {Decision-making under uncertainty, Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Hogewind2023safe,

title = {Safe Reinforcement Learning From Pixels Using a Stochastic Latent Representation},

author = {Yannick Hogewind and Thiago D. Simão and Tal Kachman and Nils Jansen},

url = {https://openreview.net/forum?id=b39dQt_uffW},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {ICLR},

keywords = {Decision-making under uncertainty, Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Simao2023safe,

title = {Safe Policy Improvement for POMDPs via Finite-State Controllers},

author = {Thiago D. Simão and Marnix Suilen and Nils Jansen},

url = {https://arxiv.org/abs/2301.04939},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {AAAI},

keywords = {Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:journals/corr/abs-2204-00755,

title = {Safe Reinforcement Learning via Shielding for POMDPs},

author = {Steven Carr and Nils Jansen and Sebastian Junges and Ufuk Topcu},

url = {https://arxiv.org/abs/2204.00755},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {To be presented at AAAI 2023},

keywords = {Decision-making under uncertainty, Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:journals/corr/abs-2210-05989,

title = {Probabilities Are Not Enough: Formal Controller Synthesis for Stochastic  Dynamical Models with Epistemic Uncertainty},

author = {Thom S. Badings and Licio Romao and Alessandro Abate and Nils Jansen},

url = {https://arxiv.org/abs/2210.05989},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

booktitle = {AAAI},

keywords = {Decision-making under uncertainty, Robustness},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Keizers2022ESREL,

title = {Atmospheric Corrosion Prognostics Using a Particle Filter},

author = {Luc Stefan Keizers and Richard Loendersloot and Tiedo Tinga},

year  = {2022},

date = {2022-08-28},

urldate = {2022-08-28},

booktitle = {Proceedings of the 32nd European Safety and Reliability Conference (ESREL 2022)},

pages = {1259–1266},

keywords = {Bayesian filters, Prognostics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/nfm/BasgozeVKKS22,

title = {BDDs Strike Back - Efficient Analysis of Static and Dynamic Fault Trees},

author = {Daniel Basgöze and Matthias Volk and Joost-Pieter Katoen and Shahid Khan and Mariëlle Stoelinga},

url = {https://dl.acm.org/doi/10.1007/978-3-031-06773-0_38},

doi = {10.1007/978-3-031-06773-0_38},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {NFM},

volume = {13260},

pages = {713–732},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Decision tree, Fault tree analysis},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:journals/corr/abs-2205-15827,

title = {Robust Anytime Learning of Markov Decision Processes},

author = {Marnix Suilen and Thiago D. Simão and David Parker and Nils Jansen},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {NeurIPS},

keywords = {Decision-making under uncertainty, Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{jimenez2022data,

title = {Data-Driven Inference of Fault Tree Models Exploiting Symmetry and Modularization},

author = {Lisandro Arturo Jimenez-Roa and Matthias Volk and Mariëlle Stoelinga},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {International Conference on Computer Safety, Reliability, and Security},

pages = {46–61},

organization = {Springer},

keywords = {Fault tree analysis, Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{jimenez2022deterioration,

title = {Deterioration modeling of sewer pipes via discrete-time Markov chains: A large-scale case study in the Netherlands},

author = {Lisandro A Jimenez-Roa and Tom Heskes and Tiedo Tinga and Hajo JA Molegraaf and Mariëlle Stoelinga},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {32nd European Safety and Reliability Conference, ESREL 2022: Understanding and Managing Risk and Reliability for a Sustainable Future},

pages = {1299–1306},

keywords = {Model learning, Prognostics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/cav/BadingsJJSV22,

title = {Sampling-Based Verification of CTMCs with Uncertain Rates},

author = {Thom S. Badings and Nils Jansen and Sebastian Junges and Mariëlle Stoelinga and Matthias Volk},

url = {https://arxiv.org/abs/2205.08300},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {CAV (2)},

volume = {13372},

pages = {26–47},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {Decision-making under uncertainty, Model checking, Scenario optimization},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Kerkkamp2021,

title = {Grouping of Maintenance Actions with Deep Reinforcement Learning and Graph Convolutional Networks},

author = {David Kerkkamp and Zaharah A. Bukhsh and Yingqian Zhang and Nils Jansen},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {International Conference on Agents and Artificial Intelligence (ICAART)},

keywords = {Machine learning, Maintenance optimization},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/aaai/BadingsA00PS22,

title = {Sampling-Based Robust Control of Autonomous Systems with Non-Gaussian  Noise},

author = {Thom S. Badings and Alessandro Abate and Nils Jansen and David Parker and Hasan A. Poonawala and Mariëlle Stoelinga},

url = {https://ojs.aaai.org/index.php/AAAI/article/view/21201/20950},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

booktitle = {AAAI},

pages = {9669–9678},

publisher = {AAAI Press},

keywords = {Decision-making under uncertainty, Model checking, Robustness},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{JimenezRoa2021_ESREL,

title = {Fault Trees, Decision Trees, and Binary Decision Diagrams: A systematic comparison},

author = {Lisandro A. Jimenez-Roa and Tom Heskes and Mariëlle Stoelinga},

editor = {Bruno Castanier and Marko Cepin and David Bigaud and Christophe Bérenguer},

url = {http://esrel2021.org/en/index.html},

doi = {10.3850/978-981-18-2016-8_241-cd},

year  = {2021},

date = {2021-09-21},

urldate = {2021-09-21},

booktitle = {Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)},

pages = {673–680},

publisher = {Research Publishing},

abstract = {In reliability engineering, we need to understand system dependencies, cause-effect relations, identify critical components, and analyze how they trigger failures. Three prominent graph models commonly used for these purposes are fault trees (FTs), decision trees (DTs), and binary decision diagrams (BDDs). These models are popular because they are easy to interpret, serve as a communication tool between stakeholders of various backgrounds, and support decision-making processes. Moreover, these models help to understand real-world problems by computing reliability metrics, minimum cut sets, logic rules, and displaying dependencies. Nevertheless, it is unclear how these graph models compare. Thus, the goal of this paper is to understand the similarities and differences through a systematic comparison based on their (i) purpose and application, (ii) structural representation, (iii) analysis methods, (iv) construction, and (v) benefits & limitations. Furthermore, we use a running example based on a Container Seal Design to showcase the models in practice. Our results show that, given that FTs, DTs, and BDDs have different purposes and application domains, they adopt different structural representations and analysis methodologies that entail a variety of benefits and limitations, the latter can be addressed via conversion methods or extensions. Specific remarks are that BDDs can be considered as a compact representation of binary DTs, since the former allows sub-node sharing, which makes BDDs more efficient at representing logical rules than binary DTs. It is possible to obtain cut sets from BDDs and DTs and construct a FT using the (con/dis)junctive normal form, although this may result in a sub-optimal FT structure.},

note = {European Safety and Reliability Conference 2021, ESREL 2021 ; Conference date: 19-09-2021 Through 23-09-2021},

keywords = {Decision trees, Fault tree analysis, Reliability engineering},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{daSilveria2021_PHM,

title = {Data Selection Criteria for the Application of Predictive Maintenance to Centrifugal Pumps},

author = {Nubia Nale Alves Silveira and Richard Loendersloot and Annemieke Angelique Meghoe and Tiedo Tinga},

url = {https://phm-europe.org/},

year  = {2021},

date = {2021-06-01},

urldate = {2021-06-01},

booktitle = {Proceedings of the 6th European Conference of the Prognostics and Health Management Societ},

number = {1},

pages = {372–380},

series = {Archives of the PHM Society European Conference},

abstract = {The maintenance of vehicles and components is present in most people's daily lives, ranging from changing a private vehicle's oil to the failure prediction of an aircraft component during flight. Usually, the manufacturer's maintenance recommendation is a good solution when the cost is not too high, and the real application is used as indicated by the manufacturer. However, this recommendation can turn unfeasible when there is a significant variation in operational conditions or high maintenance costs. In these cases, the manufacturer's suggestion is typically conservative, leading to unnecessarily high costs. Therefore, the challenge is to find the best approach for optimizing a component's maintenance, given the system in which it is integrated and the associated operational and environmental conditions. Nevertheless, the available information on the loads on the component also plays a role in that choice. This paper proposes to combine case-specific information with generic degradation prediction models to obtain an acceptable but also affordable approach. The objective is to develop data selection criteria to indicate the parameters that have a high impact on the failure prediction, in this case, of a generic impeller pump. Subsequently, the approach delivers to the user an indication of the component remaining useful life using different operational scenarios.},

note = {6th European Conference of the Prognostics and Health Management Society, PHME 2021, PHME 2021 ; Conference date: 28-06-2021 Through 02-07-2021},

keywords = {Prognostics, Sensors},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Badings2021NFM,

title = {Balancing Wind and Batteries: Towards Predictive Verification of Smart  Grids},

author = {Thom S. Badings and Arnd Hartmanns and Nils Jansen and Marnix Suilen},

url = {https://arxiv.org/abs/2101.12496},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {13th NASA Formal Methods Symposium},

keywords = {Model checking},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Simao2021alwayssafe,

title = {AlwaysSafe: Reinforcement Learning Without Safety Constraint Violations During Training},

author = {Thiago D. Simão and Nils Jansen and Matthijs T. J. Spaan},

url = {https://ifaamas.org/Proceedings/aamas2021/pdfs/p1226.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS)},

pages = {1226-1235},

publisher = {IFAAMAS},

keywords = {Machine learning},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{cubuktepe-et-al-aaai-2021,

title = {Robust Finite-State Controllers for Uncertain POMDPs},

author = {Murat Cubuktepe and Nils Jansen and Sebastian Junges and Ahmadreza Marandi and Marnix Suilen and Ufuk Topcu},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

booktitle = {35th AAAI Conference on Artificial Intelligence},

keywords = {Decision-making under uncertainty},

pubstate = {published},

tppubtype = {inproceedings}

}