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International Journal of Approximate Reasoning (IJAR)

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Impact Factor:
2.8
Publisher:
Elsevier
ISSN:
0888-613X
Viewed:
35201
Tracked:
20

Call For Papers

International Journal of Approximate Reasoning (IJAR) is an academic journal published by Elsevier. (ISSN 0888-613X, impact factor 2.8, CCF B).

Aims & Scope Uncertainty in Intelligent Systems The International Journal of Approximate Reasoning is intended to serve as a forum for the treatment of imprecision and uncertainty in Artificial and Computational Intelligence, covering both the foundations of uncertainty theories, and the design of intelligent systems for scientific and engineering applications. It publishes high-quality research papers describing theoretical developments or innovative applications, as well as review articles on topics of general interest. Relevant topics include, but are not limited to, probabilistic reasoning and Bayesian networks, imprecise probabilities, random sets, belief functions (Dempster-Shafer theory), possibility theory, fuzzy sets, rough sets, decision theory, non-additive measures and integrals, qualitative reasoning about uncertainty, comparative probability orderings, game-theoretic probability, default reasoning, nonstandard logics, argumentation systems, inconsistency tolerant reasoning, elicitation techniques, philosophical foundations and psychological models of uncertain reasoning. Domains of application for uncertain reasoning systems include risk analysis and assessment, information retrieval and database design, information fusion, machine learning, data and web mining, computer vision, image and signal processing, intelligent data analysis, statistics, multi-agent systems, etc. The journal is affiliated with the Society for Imprecise Probability: Theories and Applications (SIPTA), and Beliefs functions and Applications Society (BFAS).
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Special Issues

Special Issue on Papers in Memory of Thomas Augustin Submission Date: 2026-12-31 On January 10, 2026, Professor Thomas Augustin passed away. He was the head of the working group Methodological Foundations of Statistics and Their Applications within the Department of Statistics at LMU Munich. Throughout his career, he made decisive contributions to the advancement of imprecise probabilities, being already present at the very first ISIPTA conference in Gent in 1999 and contributing decisively to the creation of the SIPTA society in 2002. In order to pay homage to his legacy, the International Journal of Approximate Reasoning is devoting a special issue to papers broadly related to his work. This special issue is open to all those contributions that are related to Thomas' work on statistics and imprecise probabilities. In particular, topics of interest include, but are not limited to: Statistical inference with imprecise data and/or imprecise probabilities. Decision making under severe uncertainty. Machine learning with imprecise information. Partial identification and analysis of deficient data. Imprecise probabilities for survey- and official statistics. Philosophical foundations and history of imprecise probabilities. Imprecision and indeterminacy in probabilities in applied statistics. Philosophical foundations and history of statistics Measurement error models with and without imprecise probabilities Guest editors: Dr. Christoph Jansen (Executive Guest Editor), Lancaster University, Lancaster, UK; Email: [email protected] Dr. Georg Schollmeyer, Ludwig-Maximilians-Universität München, Munich, Germany; Email: [email protected] Dr. Julian Rodemann, CISPA Helmholtz Center for Information Security, Saarbrücken, Germany; Email: [email protected] Dr. Rudolf Seising, Research Institute for the History of Science and Technology, Munich, Germany; Email: [email protected] Manuscript submission information: Important Dates: Submission Open Date: May 15, 2026 Submission Deadline: December 31, 2026 Notification of Acceptance: June 30, 2027 Manuscripts must be submitted via the International Journal of Approximate Reasoning online submission system (Editorial Manager®). Please select the article type “VSI: Memory of Thomas Augustin” when submitting your manuscript online. Please refer to the Guide for authors to prepare your manuscript. All submitted papers under this call will undergo the standard review process of the journal. For any further information, the authors may contact the Guest Editors. Keywords: statistical inference with imprecise data and/or imprecise probabilities; decision making under severe uncertainty; machine learning with imprecise information; philosophical foundations and history of imprecise probabilities; measurement error models
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Special Issue on Numbers of the Future: Dealing with Uncertain Data for Quantitative Risk Analysis Submission Date: 2027-02-28 Risk is an important consideration across multiple disciplines such as: engineering, industry, healthcare, finance, and forensics. Quantitative risk analysis based on empirical, experimental or expert-elicited data will give a numerical measure of risk. However, the trustworthiness and reliability of the result is vulnerable to the level of quality and availability of the data that is used. Coupled with the (often) complex computations involved, the data and calculations need to be reliable, trackable, reusable, comprehensively described and linked, whilst safeguarding private information. The combination of all these factors introduces significant challenges and elements of uncertainty into the overall quantitative risk analysis. This begets the following fundamental research questions: • What details are needed when collecting and sharing observational data and calculations? • How can we be sure that empirical effort produces meaningful, correct, and logically complete measurements? • What changes or augmentations are needed in empirical work to ensure that estimates and calculations are trackable and checkable? • What structures and processes can make scientific statements trustworthy, beyond relying on the integrity of scientists as individuals? • How can these be automated to be natural and least burdensome? • How can we radically reduce the need to ’clean’ data sets? • What provisions can guarantee that the information is secure and uncorrupted but also accessible and reusable? • How can we avoid wasting or losing observations? • What are the ethical considerations around anonymisation of data? Guest editors: Adolphus Lye (Executive Guest Editor), Singapore Nuclear Research and Safety Institute, National University of Singapore, Singapore; Email: [email protected] Nicholas Gray, Institute of Population Health, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK; Email: [email protected] Alexander Wimbush, Cancer Research Clinical Trials Unit, School of Medical Sciences, University of Birmingham, Birmingham, UK; Email: [email protected] Yu Chen, Department of Mechanical and Aerospace Engineering, University of Liverpool, Liverpool, UK; Email: [email protected] Kari Sentz, Los Alamos National Laboratory, Los Alamos, USA; Email: [email protected] Special issue information: The objective of this special issue is to create a collection of the state-of-the-art methodologies and cutting-edge research results in the context of risk analysis across multiple disciplines, aimed at addressing the above research questions. Topics of interest to the special issue include (but not limited to): • Dealing with uncertainty from expert elicitations • Dimension and units checking and propagation • Decision-making under justification tracking • Provenance and calculation stream histories • Evidence and justification tracing • Ethical dimensions of numbers and data • Truthfulness of numbers reported in crisis situations Note that all contributions should explicitly highlight and address the challenges in risk analysis due to uncertain data. The Special Issue is inspired by the works presented at the inaugural “Numbers of the Future” conference held at the University of Liverpool, United Kingdom, between the 3rd and 5th December 2025. Extended versions of the research works presented at that conference are welcomed. Contributions from researchers and practitioners beyond the conference are also welcomed. Manuscript submission information: Important Dates: Submission Open Date: April 13, 2026 Submission Deadline: February 28, 2027 Notification of Acceptance: May 31, 2027 Manuscripts must be submitted via the International Journal of Approximate Reasoning online submission system (Editorial Manager®). Please select the article type “VSI: Numbers of the Future” when submitting your manuscript online. Please refer to the Guide for authors to prepare your manuscript. All submitted papers under this call will undergo the standard review process of the journal. For any further information, the authors may contact the Guest Editors. Keywords: Uncertainty quantification; Risk analysis; Trustworthiness; Data analytics; Security
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