Re: CfP #2: Special Issue on Information Sciences "Modeling imprecise information and knowledge to improve explanability in AI"

please notice that late submissions are still accepted. Prospective
authors should contact [email protected] for further information.

On Wednesday, 2 February 2022 at 21:51:03 UTC+1, Corrado Mencar wrote:
> (Apologies for cross-postings)
>
> https://www.journals.elsevier.com/information-sciences/call-for- papers/modeling-imprecise-information-and-knowledge-to-improve-
> explanability-in-ai
>
> *Aims and scope*
>
> XAI lies at the intersection of different fields, which include, let
> alone Artificial Intelligence, Cognitive and Social Sciences, Human
> Computer Interaction, Philosophy and Psychology among others. The
> strong multidisciplinary character of XAI is due to the centrality of
> people in all aspects of the development and deployment of XAI
> systems. People have an exceptional ability to manage the complexity
> of phenomena through mental processes such as organization,
> granulation and causation. A key factor is the capability of managing
> imprecision in forms that are well captured by several theories within
> the Granular Computing paradigm, such as Fuzzy Set Theory, Rough Set
> Theory, Interval Computing and hybrid theories among others. Endowing
> XAI systems with the ability of dealing with the many forms of
> imprecision, not only in the inference processes that lead to
> automated decisions, but also in providing explanations, is a key
> challenge that can push forward current XAI technologies towards more
> trustworthy systems and full collaborative intelligence.
>
> Topics of interest include, but are not limited to:
>
> - Foundational and philosophical aspects of imprecision in information
>   and knowledge
> - Theoretical advancements in imprecision modeling in AI
> - Imprecision modeling methods to improve explainability in AI New
>   technologies for representing and processing imprecision in XAI
>   systems
> - Real-world applications and case studies that demonstrate
>   explainability improvements through imprecision management
>
> *Submission guidelines and review process*
>
> Papers must be submitted according to the standard procedure of
> Information Sciences, selecting the S.I. "Managing imprecision and
> uncertainty in XAI systems”. All submitted papers should report
> original work and provide meaningful contributions to the current
> state of the art.
>
> Each submitted paper will undergo a first screening by the Guest
> Editors. If the submission falls within the scope of the SI, it will
> undergo a regular revision process. Acceptance criteria are the same
> of regular issues of the journal.
>
> *Important dates*
>
> - Submission start: November 1st, 2021
> - Paper submission deadline: January 28th, 2022 (If a few more days
>   are needed, please contact the GEs for a possible extension)
> - Notification of first-round review results: July 15th, 2022
> - Tentative period for final publication: Fall 2022
>
> Authors guidelines and journal information can be found at https://www.journals.elsevier.com/information-
> sciences
>
> *Guest Editors*
>
> Angelo Ciaramella - Università degli Studi di Napoli Parthenope, Italy
> Corrado Mencar - Università degli Studi di Bari Aldo Moro, Italy
> Susana Montes - Universidad de Oviedo, Spain Stefano Rovetta -
> Università degli Studi di Genova, Italy
>
> For any information, please contact Corrado Mencar
> <[email protected]>