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).

Special Issue on Combining, Modelling and Analyzing Imprecision, Randomness and Dependence
Submission Date: 2024-12-31

The aim of this special issue is to present a peer-reviewed collection of papers addressing the latest advances in soft methods in probability and statistics, in particular those discussed and elaborated at the 11th International Conference on Soft Methods in Probability and Statistics (SMPS 2024).

The SMPS 2024 covered a broad variety of topics ranging from core SMPS competencies like fuzzy sets, imprecise and generalized probabilities, random sets, and T-norms to classification, clustering, decision theory, dependence modeling and robust statistics as well as bridging to topical disciplines such as functional data analysis, optimal transport and machine learning. The emphasis of the special issue will be on papers on the interplay between at least two components out of the following three: Imprecision, Randomness and Dependence.

Guest editors:

Dr. Sebastian Fuchs (Executive Guest Editor)
Department for Artificial Intelligence and Human Interfaces, Paris Lodron University of Salzburg, Austria
Email: sebastian.fuchs@plus.ac.at
Areas of expertise: multivariate and nonparametric statistics, dependence modeling, computational statistics and data analytics

Prof. Dr. Wolfgang Trutschnig
Department for Artificial Intelligence and Human Interfaces, Paris Lodron University of Salzburg, Austria
Email: wolfgang.trutschnig@plus.ac.at
Areas of expertise: multivariate and nonparametric statistics, dependence modeling, statistics with imprecise data/information

Manuscript submission information:

Tentative Schedule:

    Submission Open Date: October 15, 2024
    Final Submission Deadline: December 31, 2024
    Notification of Acceptance: August 1, 2025

Manuscripts must be invited by the Guest Editors and submitted via the International Journal of Approximate Reasoning online submission system (Editorial Manager): https://www.editorialmanager.com/ija/default.aspx. Please select the article type “VSI: SMPS 2024” when submitting your manuscript online.

Please refer to the Guide for Authors to prepare your manuscript: https://www.sciencedirect.com/journal/international-journal-of-approximate-reasoning/publish/guide-for-authors

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:

classification; clustering; decision theory; dependence modeling; functional data analysis; fuzzy sets; imprecise / generalized probabilities; industrial applications; machine learning; optimal transport; random sets; reliability; robust statistics; soft computing; statistics with imprecise data; times series; t-norms

Special Issue on Extended papers from the Twelfth International Conference on Probabilistic Graphical Models
Submission Date: 2025-01-31

Probabilistic graphical models (PGMs) are a popular tool with remarkable impact on AI and Statistics, given their clear semantics and interpretability.

This special issue will include extended versions of selected papers from the 12th International Conference of Probabilistic Graphical Models (PGM 2024).

This Special Issue seeks original contributions covering all aspects of PGMs, including their construction, analysis, inference, explanation and application. Both theoretical papers and contributions including a thorough experimental analysis of the methodological advances are within the scope of this Special Issue.

Guest editors:

Dr. Silja Renooij (Executive Guest Editor)Department of Information and Computing Sciences, Utrecht University, the NetherlandsEmail: s.renooij@uu.nl Areas of Expertise: construction, analysis and explanation of probabilistic graphical models

Dr. Johan KwisthoutDonders Institute for Brain, Cognition and Behaviour, Radboud University, the NetherlandsEmail: j.kwisthout@donders.ru.nl Areas of Expertise: computational complexity aspects of probabilistic model

Dr. Janneke BoltDepartment of Information and Computing Sciences, Utrecht University, the NetherlandsEmail: j.h.bolt@uu.nl Areas of Expertise: fundamentals of independence and inference in probabilistic graphical models

Manuscript submission information:

Tentative Schedule:

Submission Open Date: October 1, 2024
Final Submission Deadline: January 31, 2025
Notification of Acceptance: November 1, 2025

Special Issue on Logics for the new AI spring 2
Submission Date: 2025-03-03

The development of logics capable to perform human-like reasoning is one of the central objectives around which the logical community of Artificial Intelligence (AI) moved its first steps. Besides being a fundamental tool of knowledge representation and reasoning, logical tools are expected to play a key role in the future of AI especially owing to their ability to integrate symbolic and sub-symbolic AI.

The scope of the special issue includes, but is not limited to the following topics
- Logical methods in symbolic AI
- Logical methods in machine learning
- Machine learning in a logical setting
- Reasoning and (interactive) decision making under uncertainty
The proposed Special Issue would be the second edition of the IJAR special issue “Logics for the new AI Spring”.

Guest editors:
Dr. Tommaso Flaminio (Executive Guest Editor)IIIA-CSIC, Barcelona, SpainEmail: tommaso@iiia.csic.es
Prof. Hykel HosniLUCI, Milano, ItalyEmail: hykel.hosni@unimi.it

Manuscript submission information:

Tentative Schedule:

Submission Open Date: September 9, 2024
Final Submission Deadline: March 3, 2025
Notification of Acceptance: January 31, 2026