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PhD student opportunity - Prognostics and Health Management solutions for Reliable Autonomous Systems
by Joxe Inaxio Aizpurua July 6, 2022

July 6, 2022

*Prognostics and Health Management solutions for* *Reliable Autonomous Systems* *Description* The revolution in robotics and autonomous systems (RAS) is unstoppable. The advance of autonomous system applications, such as autonomous transport [1, 2] and autonomous inspections [3], generate multiple benefits for the industry and society, including the improved driving security in autonomous transport, and improved reliability of critical and remote infrastructure through specialized robots and drones. However, the reliability assurance of RAS is a complex challenge, as it requires incorporating advanced intelligence that should evolve according to run-time operation [4]. The challenging yet exciting, operation context of RAS, hampers the reliability assurance of RAS, which decelerates the acceptance and everyday use of RAS. Different technological solutions have emerged to improve the design and reliability of RAS [5]. Most of the technological configurations include a combination of mechanical and electrical components, along with onboard software intelligence to adopt decisions without direct human intervention. In this context, using the ever-increasing prognostics and health management solutions, it is possible to develop a prognostics modelling approach for RAS health monitoring using reliability, machine learning, uncertainty modelling and optimization methods [6]. The project’s objective is to develop novel prognostics methods for RAS, which can accurately inform about the model’s confidence in the decisions in real-time and the way to mitigate the existing problem via optimization methods, and always, provide a worst-case estimate on its predictions by using a proper modelling and update of the different sources of uncertainty. In particular, the work will focus on the integration of uncertainties to make prognostic predictions robust, using concepts such as adversarial learning, combined with statistical learning and artificial intelligence methods. The models developed in this project will be validated with the data collected from industry partners that work with autonomous robots focusing on (i) autonomous remote inspections for renewable energy and (ii) automotive industry. The project will be developed in <https://www.mondragon.edu/en/home>Mondragon Unibertsitatea within the Electronics and Computer Science Department, in collaboration between the Data Analytics and Signal Processing and Communications groups. Throughout the thesis, the student will engage continuously with industry and stays at different universities and/or research centers will be pursued. Interested applicants, send your CV and a short motivation letter to: jiaizpurua(a)mondragon.edu and ezugasti(a)mondragon.edu Application deadline. Review of applications will begin July 1st and continue until the position is filled. *Requirements* - M.Sc. degree in telecommunications, electronics, computer science, mathematics, embedded systems or a related area. - Programming skills: Matlab, Python, R, or C++ (samples from prior projects or a GitHub repository are preferred) - Statistics/mathematics, data science/AI/ML - Knowledge/experience with autonomous systems is a plus. - Knowledge/experience with reliability and/or diagnostics/health management methods is a plus. - Experience with artificial intelligence / optimization methods is a plus. *References* [1] Feng, S., Yan, X., Sun, H. et al. Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment. *Nature Communications* 12, 748 (2021). <https://doi.org/10.1038/s41467-021-21007-8> https://doi.org/10.1038/s41467-021-21007-8 [2] Ellefsen, A. L., Æsøy, V., Ushakov, S., & Zhang, H. (2019). A comprehensive survey of prognostics and health management based on deep learning for autonomous ships. IEEE Transactions on Reliability, 68(2), 720-740 [3] Floreano, D., & Wood, R. J. (2015). Science, technology and the future of small autonomous drones. *nature*, *521*(7553), 460-466. [4] Aslansefat, K., Kabir, S., Abdullatif, A., Vasudevan, V., & Papadopoulos, Y. (2021). Toward Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition Systems. *Computer*, *54*(8), 66-76. [5] Elghazel, W., Bahi, J., Guyeux, C., Hakem, M., Medjaher, K., & Zerhouni, N. (2015). Dependability of wireless sensor networks for industrial prognostics and health management. Computers in Industry, 68, 1-15. [6] Aizpurua, J. I., Catterson, V. M., Papadopoulos, Y., Chiacchio, F., & Manno, G. (2017). Improved dynamic dependability assessment through integration with prognostics. *IEEE Transactions on Reliability*, *66*(3), 893-913. -- *Joxe Aizpurua.*

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Second SIPTA seminar: 29th of June, at 15:00 CEST, Ruobin Gong talking about "Imprecise probabilities in modern data science: challenges and opportunities"
by Sébastien Destercke June 17, 2022

June 17, 2022

Dear SIPTiAns and IP enthusiasts, We are delighted to announce our second SIPTA online seminar on imprecise probabilities (IP). These monthly events are open to anyone interested in IP, and will be followed by a Q&A and open discussion. They also provide an occasion for the community to meet, keep in touch and exchange between in-person events. For this second seminar, we are very happy to have Ruobin Gong as our speaker. After a PhD at Harvard, she is now assistant professor at Rutgers, working at the crossroad of imprecise probabilities, statistics and data science. On the 29th of June, at 15:00 CEST (up to 17:00 CEST, with a talk duration of 45min/1h), she will talk about "Imprecise probabilities in modern data science: challenges and opportunities”. Curious? Then check out the abstract on the webpage of the SIPTA seminars: sipta.org/events/sipta-seminars. The zoom link for attending the seminar will appear on that same page shortly before the event. So please mark your calendars on the 29th of June, 15:00 CEST, and join us for the occasion. And for those who missed the previous seminar and want to catch up, or simply want to see it again and again, it is now online at https://www.youtube.com/channel/UCPER8Dfil66KZCYlsK86XCQ/featured. See you at the seminar! Sébastien, Enrique and Jasper

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Looking for test cases for imprecise/conditional probabilistic satisfiability/coherence checking
by Quaeghebeur, Erik June 15, 2022

June 15, 2022

Dear SIPTA list, After having lain dormant, research on the CONEstrip algorithms [*] has awakened again. These algorithms are essentially meant for checking coherence of general sets of desirable gambles. This is very closely related to checking coherence of imprecise or conditional probability assessments and probabilistic satisfiability (PSAT). The classical CONEstrip algorithm assumes gambles are directly specified (as vectors); this corresponds to having an explicit description of the possibility space. The propositional CONEstrip algorithm assumes gambles are expressed as linear combinations of propositional sentences; this corresponds to specifying (imprecise/conditional) probabilities for events and relationships between events, but leaving the underlying possibility space implicit. A collaborator is working with my support on creating implementations and evaluating these. For the evaluation, we want to use realistic test cases. These are nontrivial to construct, certainly for the propositional context. Therefore, we are looking for such test cases. So I would like to ask you to send me any information you may have about existing test cases of this kind (or ones that are ‘close enough’). This can be in the form of pointers to papers with a description of one or more problems that may function as test cases or as pointers to files containing test cases encoded in some documented format. I am grateful for any input. Best regards, Erik [*] https://ac.erikquaeghebeur.name/?search=conestrip -- https://ac.erikquaeghebeur.name

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[UAI 2022] Call for Participation: Registration open & student scholarships available
by De Campos, Cassio June 7, 2022

June 7, 2022

Dear all, We are excited to announce that the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022) will be held in Eindhoven, The Netherlands, on August 1-5, 2022. The conference accepted 36 papers for oral presentation and 194 for poster presentation and will be single-track. Below we would like to share with you some updates: 1. Registration for UAI 2022 is open: https://www.auai.org/uai2022/registration. The early bird registration deadline is June 21st. When you register, you can choose to sign up as a potential discussant for an oral presentation. Being a discussant is a great way to learn about papers and to engage with other people at the conference. For more information, please see https://www.auai.org/uai2022/discussants. 2. Students are encouraged to apply for UAI 2022 student scholarships. The deadline for this is June 15. For more information, please see https://www.auai.org/uai2022/student_scholarships. 3. We are delighted to have Danilo J. Rezende, Eric P. Xing, Finale Doshi-Velez, Mihaela van der Schaar, Peter Spirtes, and Zeynep Akata as our keynote speakers, who will share with you exciting advances in many directions pertinent to UAI. 4. We are delighted to announce that the UAI 2022 competition (https://www.auai.org/uai2022/uai2022_competition) is starting soon. We hope to see many of you at UAI 2022, either in-person or online! Best regards, Marloes Maathuis & Cassio de Campos UAI 2022 General Chairs and James Cussens & Kun Zhang UAI 2022 Program Chairs

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BELIEF2022 Call For Poster
by Sylvie Le-hegarat June 5, 2022

June 5, 2022

================================================================ 7th International Conference on Belief Functions (BELIEF 2022) Call For Participation The BELIEF 2022 Conference Committee is pleased to invite submissions of abstracts for poster presentations. The poster session aims to encourage discussions either around preliminary works or works in progress. For poster presentation, we also encourage the submission of abstracts corresponding to works in recent papers accepted or submitted elsewhere. The conference or journal where the paper was published or submitted must be specified at submission. Submissions should include a title and an abstract no longer than 250 words. If accepted, they will be presented at the conference in a special poster session but will not appear in the proceedings. The main objective of the poster session is to foster discussions around preliminary works, or to popularize newly published works, therefore poster presenters are required to participate on site to the conference. The deadline for submissions is: July 31, 2022. Poster presenters will be notified by August 8th. Conference website: [ http://hebergement.universite-paris-saclay.fr/belief2022/ | http://hebergement.universite-paris-saclay.fr/belief2022/ ] Dates: October 26th-28th, 2022 Location: Paris, France ================================================================ The organizers would be grateful if you could inform potentially interested participants of this conference. Sylvie LE HEGARAT-MASCLE professeur à POLYTECH PARIS-SACLAY laboratoire SATIE Bâtiment 660 (Digiteo-Shannon), rue Noetzlin 91405 Orsay Cedex

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Re: SUM 2022: deadline extended to June 13
by Kreinovich, Vladik May 26, 2022

May 26, 2022

FYI, papers related to imprecise probabilities are welcome at this series of conferences From: Lluis Godo Sent: Thursday, May 26, 2022 12:15 AM *** 15th International Conference on Scalable Uncertainty Management (SUM 2022) *** *** Paris, France, October 17-19, 2022 *** Dear colleague, Apologies if you receive multiple copies. Please forward this call to interested parties. We have extended the submission deadline for SUM 2022 to **June 13, 2022** (no need to submit an abstract). We are happy to announce that the following talks and tutorials have been confirmed so far: _Invited Talks:_ - Silja Renooij - TBA - Francesca Toni - TBA _Tutorials____(there will be other tutorials):_ - Christophe Gonzales - Decision under Uncertainty - Denis Bouyssou - Preference Modelling - Diedrich Wolter - Geometric and Logic Commitments in Knowledge Graph - Jean-Guy Mailly - Constrained Incomplete Argumentation Frameworks - Jeremy Rohmer - Dealing with Imperfect Knowledge in Natural Hazard Assessments: Beyond Classical Probabilities and Challenges - Michael Poss - Robustness in Optimisation - Tanya Braun - Statistical Relational Learning **** We want to reassure authors that we are monitoring the coronavirus situation and exploring contingency plans for a virtual conference should a physical conference not be possible. Regardless, the proceedings will go ahead and will be published this year. **** Best regards Florence, Meltem, Nico ======================================================================== Call for Papers ======================================================================== The 15th International Conference on Scalable Uncertainty Management (SUM 2022) will be held in Paris, France from October 17-19, 2022. See: https://sum2022.sciencesconf.org ======================================================================== Description ======================================================================== Established in 2007, the SUM conferences are annual events which aim to gather researchers with a common interest in managing and analyzing imperfect information from a wide range of fields, such as Artificial Intelligence and Machine Learning, Databases, Information Retrieval and Data Mining, the Semantic Web and Risk Analysis, and with the aim of fostering collaboration and cross-fertilization of ideas from the different communities. An originality of the SUM conferences is their care for dedicating a large space of their program to tutorials covering a wide range of topics related to uncertainty management. Each tutorial provides a survey of one of the research areas in the scope of the conference. ======================================================================== Topics of Interest ======================================================================== We solicit papers on the management of large amounts of complex kinds of uncertain, incomplete, or inconsistent information. We are particularly interested in papers that focus on bridging gaps, for instance between different communities, between numerical and symbolic approaches, or between theory and practice. Topics of interest include (but are not limited to): Imperfect information in databases - Methods for modeling, indexing, and querying uncertain databases - Top-k queries, skyline query processing, and ranking - Approximate, fuzzy query processing - Uncertainty in data integration and exchange - Uncertainty and imprecision in geographic information systems - Probabilistic databases and possibilistic databases - Data provenance and trust - Data summarization - Very large datasets Imperfect information in information retrieval and semantic web applications - Approximate schema and ontology matching - Uncertainty in description logics and logic programming - Learning to rank, personalization, and user preferences - Probabilistic language models - Combining vector-space models with symbolic representations - Inductive reasoning for the semantic web Imperfect information in artificial intelligence - Statistical relational learning, graphical models, probabilistic inference - Argumentation, defeasible reasoning, belief revision - Weighted logics for managing uncertainty - Reasoning with imprecise probability, Dempster-Shafer theory, possibility theory - Approximate reasoning, similarity-based reasoning, analogical reasoning - Planning under uncertainty, reasoning about actions, spatial and temporal reasoning - Incomplete preference specifications - Learning from data Risk analysis - Aleatory vs. epistemic uncertainty - Uncertainty elicitation methods - Uncertainty propagation methods - Decision analysis methods - Tools for synthesizing results ======================================================================== Submission Guidelines ======================================================================== SUM 2022 solicits original papers in the following three categories: - Long papers (14 pages): technical papers reporting original research or survey papers - Short papers (8 pages): papers reporting promising work-in-progress, system descriptions, position papers on controversial issues, or survey papers providing a synthesis of some current research trends - Extended abstracts (2 pages) of recently published work in a relevant journal or top-tier conference All SUM submissions must be formatted according to the LNCS/LNAI guidelines:https://www.springer.com/gp/computer-science/lncs/conference-pro… Papers should be submitted via EasyChair:https://easychair.org/conferences/?conf=sum2022 ======================================================================= Dates ======================================================================= All Deadlines are 23:59 Central European Time. Submission deadline: June 13, 2022 Notification: July 18, 2022 Camera-ready copies due: August 8, 2022 Conference: Oct. 17-19, 2022 ======================================================================= Publication ======================================================================= Accepted papers will be published by Springer in the Lecture Notes in Artificial Intelligence (LNAI) series. Authors of an accepted paper will be expected to sign copyright release forms, and one author is expected to give a presentation at the conference. ======================================================================== Organization ======================================================================== Meltem Öztürk-Escoffier (Université Paris-Dauphine - PSL), General Chair Florence Dupin de Saint-Cyr (IRIT, Université Toulouse 3), PC Co Chair Nico Potyka (Imperial College London), PC Co Chair ======================================================================== PC Members ======================================================================== Leila Amgoud, IRIT - CNRS Alessandro Antonucci, IDSIA Nahla Ben Amor, Institut Supérieur de Gestion de Tunis Salem Benferhat, Cril, CNRS UMR8188, Université d'Artois Leopoldo Bertossi, Universidad Adolfo Ibanez, Santiago, Chile & Skema Business School, Montreal, Canada Fernando Bobillo, University of Zaragoza Imen Boukhris, LARODEC - Université de Tunis- ISG Tunis Rafika Boutalbi, University of Stuttgart Tanya Braun, University of Münster Davide Ciucci, Università di Milano-Bicocca Fabio Cozman, University of São Paulo Thierry Denoeux, Universite de Technologie de Compiegne Sylvie Doutre, University of Toulouse 1 - IRIT Zied Elouedi, Université de Tunis Lluis Godo, Artificial Intelligence Research Institute, IIIA - CSIC Manuel Gómez-Olmedo, Univ. de Granada Christophe Gonzales, Aix-Marseille Université, LIS, France John Grant, Towson University Arjen Hommersom, Open University of the Netherlands Eric Lefevre, LGI2A Université d'Artois Philippe Leray, LINA/DUKe - Nantes University Thomas Lukasiewicz, University of Oxford Francesca Mangili, IDSIA Silviu Maniu, Universite Paris-Sud Thomas Meyer, University of Cape Town and CAIR Serafin Moral, University of Granada Francesco Parisi, DIMES - University of Calabria Henri Prade, IRIT - CNRS Andrea Pugliese, University of Calabria Benjamin Quost, HeuDiaSyC laboratory, University of Technology of Compiègne Steven Schockaert, Cardiff University Umberto Straccia, ISTI-CNR Andrea Tettamanzi, Univ. Nice Sophia Antipolis Matthias Thimm, FernUniversität in Hagen Maurice van Keulen, University of Twente Barbara Vantaggi, Sapienza --

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First sipta seminar: it's monday, 15:00 CEST
by Sébastien Destercke May 25, 2022

May 25, 2022

Dear IP enthusiasts, This is a small mesage to remind you all that the very first SIPTA seminar will take place this monday. To say that we are very much looking forward to it would be an understatement. Here are some key information: Speaker: Gert de Cooman Title: Imprecision, not as a problem, but as part of the solution Zoom link: https://utc-fr.zoom.us/j/84038691673 Abstract: Imprecision in probability theory is often considered to be unfortunate, something to be tolerated, and then only if there is no other way out. In this talk, I will argue that imprecision also has strongly positive sides, and that it can allow us to look at, approach and deal with existing problems in novel ways. I will provide a number of examples to corroborate for this thesis, based on my research experience in a number of fields: inference and decision making, stochastic processes, algorithmic randomness, game-theoretic probability, functional analysis, ... Be sure to take a look at https://sipta.org/events/sipta-seminars/ where you can find additional information. See you on monday! Sébastien, Enrique and Jasper

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FW: date change for NAFIPS'2024 conference
by Kreinovich, Vladik May 18, 2022

May 18, 2022

FYI, papers related to imprecise probabilities are always welcome at this series of conferences. ************************************************** Dear Friends, There was a minor change in dates for the 2024 Annual Conference of the North American Fuzzy Information Processing Society – that will be on South Padre Island, Texas, in May 2024. The new dates are May 27-29, mark your calendars! ************************************************** From: Barnabas Bede mailto:bbedeb@gmail.com At the convention center on San Padre Island the only dates available for May 2024 are May 27 - 29 that is Monday through Wednesday.

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FW: IEEE Symposium on Computational Intelligence for Engineering Solutions: CFP
by Kreinovich, Vladik May 10, 2022

May 10, 2022

FYI, papers related to imprecise probabilities are very welcome ************************************************** IEEE Symposium on Computational Intelligence for Engineering Solutions (IEEE CIES) https://www.ieeessci2022.org/symposia_cies.html Part of IEEE Series of Symposia on Computational Intelligence, Singapore, December 4-7, 2022, https://www.ieeessci2022.org/ Developments in Engineering are characterized by a growing complexity, which is balanced by an extensive utilization of computational resources. This complexity is not only a feature of engineering systems, processes and products, it is primarily a key attribute of the respective algorithms for analysis, control and decision-making to develop those engineering solutions. To cope with complexity in this broad spectrum of demands, Computational Intelligence is implemented increasingly in virtually all engineering disciplines. This emerging approach provides a basis for developments of a new quality. This Symposium is focused on the utilization of Computational Intelligence in this context in the entire field of engineering. Examples concern the control of processes of various kinds and for various purposes, monitoring with sensors, smart sensing, system identification, decision-support and assistance systems, visualization methods, prediction schemes, the solution of classification problems, response surface approximations, the formulation of surrogate models, etc. The engineering application fields may comprise, for example, bioengineering with prostheses design and control, civil and mechanical engineering processes, systems and structures concerned with vehicles, aircraft or bridges, industrial and systems engineering with design and control of power systems, electrical and computer engineering with developments in robotics, etc. All kinds of approaches from the field of Computational Intelligence are welcome. As a part of the Symposium special attention is paid to sustainable engineering solutions to address current and future challenges of environmental changes and uncertainty. This includes developments dealing with climate change, environmental processes, disaster warning and management, infrastructure security, lifecycle analysis and design, etc. Events, disasters and issues under consideration may be natural such as earthquakes or tsunamis, man-made such as human failure or terrorist attacks, or a combination thereof including secondary effects such as failures in nuclear power plants, which may be critical for systems, the environment and the society. Developments which include a comprehensive consideration of uncertainty and techniques of reliable computing are explicitly invited. These may involve probabilistic including Bayesian approaches, interval methods, fuzzy methods, imprecise probabilities and further concepts. In this context robust design is of particular interest with all its facets as a basic concept to develop sustainable engineering solutions. ********************************************************************* Topics Complex engineering systems, structures and processes Intelligent analysis, control and decision-making Management and processing of uncertainties Problem solution in uncertain and noisy environments Reliable computing Sustainable solutions Infrastructure security Climate change Environmental processes Disaster warning and management Lifecycle analysis and design Automotive systems Monitoring Smart sensing System identification Decision-support and assistance systems Visualization methods Prediction schemes Classification methods, cluster analysis Response surface approximations and surrogate models Sensitivity analysis Robust design, reliability-based design, performance-based design Risk analysis, hazard analysis, risk and hazard mitigation Optimization methods, evolutionary concepts Probabilistic and statistical methods Simulation methods, Monte-Carlo and quasi Monte-Carlo Bayesian approaches / networks Artificial Neural Networks Imprecise probabilities Evidence theory p-box approach Fuzzy probability theory Interval methods Fuzzy methods Convex modeling Information gap theory ********************************************************************* Symposium Chairs Michael Beer Leibniz University Hannover Vladik Kreinovich University of Texas at El Paso Rudolf Kruse Otto-von-Guericke University ********************************************************************* Important dates: Paper Submission: Friday, 1st July 2022 Paper Acceptance: Thursday, 1st September 2022 Full Manuscript Submission: Monday. 19th September 2022 Early Registration: Monday, 26th September 2022 Conference Dates: 4th - 7th December 2022 ********************************************************************** Submission logistics: see https://www.ieeessci2022.org/

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MPREF Final Call for Papers
by Paolo Viappiani May 10, 2022

May 10, 2022

(apologies for multiple receptions) papers dealing with imprecise probabilities and preferences are well accepted! ======================================================== M-PREF13: FINAL CALL FOR PAPERS (DEADLINE EXTENDED) 13th Multidisciplinary Workshop on Advances in Preference Handling July 23, Vienna, Austria, in conjunction with IJCAI-ECAI2022 ======================================================== Workshop website: https://sites.google.com/view/m-pref2022/ INVITED TALKS * Rudolf Vetschera, University of Wien * Haris Aziz, UNSW Sydney * Andrea Passerini, University of Trento IMPORTANT DATES * Friday, May 20, 2022: Workshop paper submission deadline (recently extended). * Monday, June 8, 2022: Notification on workshop paper submissions. * Friday, June 17, 2022: Camera-ready copy due to organizers. * July 23, 2022: M-PREF’13 Workshop. SUBMISSION Researchers interested in preference handling from AI, OR, CS or other computational fields may submit a paper (7 + 1 pages in PDF, formatted in IJCAI style) via Easy Chair system: Easy Chair : https://www.easychair.org/login.cgi?conf=mpref2022 TOPICS The workshop on Advances in Preference Handling addresses all computational aspects of preference handling. This includes methods for the elicitation, learning, modeling, representation, aggregation, and management of preferences and for reasoning about preferences. The workshop studies the usage of preferences in computational tasks from decision making, database querying, web search, personalized human-computer interaction, personalized recommender systems, e-commerce, multi-agent systems, game theory, social choice, combinatorial optimization, planning and robotics, automated problem solving, perception and natural language understanding and other computational tasks involving choices. The workshop seeks to improve the overall understanding of and best methodologies for preferences in order to realize their benefits in the multiplicity of tasks for which they are used. Another important goal is to provide cross-fertilization between the numerous sub-fields that work with preferences. * Preference handling in artificial intelligence * Preference handling in database systems * Preference handling in multiagent/multicriteria systems * Preference aggregation * Reasoning with preferences * Explaining preferences * Applications of preferences * Preference elicitation, statistical learning of preferences * Preference representation and modeling * Properties and semantics of preferences * Uncertainty in preferences * Practical preferences WORKSHOP CHAIRS * Meltem Ozturk, LAMSADE, PSL-Université Paris Dauphine * Christophe Labreuche, Thales * Paolo Viappiani, LAMSADE, PSL-Université Paris Dauphine * Sébastien Destercke, Heudiasyc, Université de Technologie de Compiègne

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