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AI
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Conceptualization and Semantic Knowledge
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Conceptualization and Semantic Knowledge

A special issue of AI (ISSN 2673-2688).

Deadline for manuscript submissions: closed (15 April 2022) | Viewed by 7497

Special Issue Editors

Dr. Farshad Badie

E-Mail Website
Guest Editor
Research Group ’Natural and Formal Languages’, Aalborg University, Aalborg, Denmark
Interests: formal/philosophical logic; logic and cognitive science; knowledge representation; symbolic AI
Dr. Luis M. Augusto

E-Mail Website
Guest Editor
Independent Researcher, Madrid, Spain
Interests: formal semantics; semantic AI; knowledge science

Special Issue Information

Dear Colleagues, 

Until recently topics solely of philosophy and psychology, conceptualization and semantic knowledge are now core concerns in AI. Questions such as “How do humans form, structure, and represent concepts?” and “How do we interpret data and information from the environment?” are now investigated from the viewpoint of what can be covered by the label “semantic AI,” which is currently undergoing redefinition. This is largely web-centered (the Semantic Web), with ontology engineering and NLP methods at the forefront of research, but new trends in AI also focus on how humans share concepts and on structures like semantic bases. In particular, we anticipate that cognitive robotics will constitute a large piece of the cake, with intensive research (re)focusing on the grounding problem and knowledge structures and systems now from a formal semantic perspective. This Special Issue encourages authors to submit their research outcomes in conceptualization and semantic knowledge, in particular output resulting from multi- and interdisciplinary work recruiting, among other fields, knowledge representation, symbolic AI, cognitive modeling, semantic technologies, etc.

Dr. Farshad Badie
Dr. Luis M. Augusto
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

19 pages, 345 KiB  
Article
An Approach to Conceptualisation and Semantic Knowledge: Some Preliminary Observations
by Hans Götzsche
AI 2022, 3(3), 582-600; https://doi.org/10.3390/ai3030034 - 22 Jun 2022
Cited by 1 | Viewed by 2201
Abstract
The paper below takes up the question of whether it is possible to transfer the notion of ‘semantic knowledge’—as a human process of making language generate and confer meanings—to machines, which have as one of their properties the capability of handling high amounts [...] Read more.
The paper below takes up the question of whether it is possible to transfer the notion of ‘semantic knowledge’—as a human process of making language generate and confer meanings—to machines, which have as one of their properties the capability of handling high amounts of information. This issue is presented in an extended introduction to the paper’s account of and solutions to this intricate problem. Thereafter, the theoretical notion of ‘knowledge’ is considered in its philosophical, and thereby scientific, context, and the basis of its modern import is pointed to being Immanuel Kant’s deliberations on a priori vs. a posteriori knowledge. The author’s solution to the predicament of modern ideas about knowledge is the proposed theory of Occurrence Logic, invented by the author, which abandons truth-values from valid reasoning, and this approach is briefly accounted for. It presupposes a theoretical model of human cognitive systems, and the author has such a model under development which, in the future, may be able to solve the question of what ‘semantic knowledge’ actually is. So far, the theoretical account in this paper points to the critical issue of whether natural language semantics can be grasped as words explaining words or must include the connection between words and objects in the world. The author is in favour of the last option. This leads to the question of the functions of the human brain as the organ connecting words with the outer world. The idea of the so-called ‘predictive brain’ is referred to as a possible solution to the brain/cognition issue, and the paper concludes with a suggestion that an emulation of the interaction between the mentioned cognitive systems may cast some new light on the field of Artificial Intelligence. Full article
(This article belongs to the Special Issue Conceptualization and Semantic Knowledge)
18 pages, 1232 KiB  
Article
The Form in Formal Thought Disorder: A Model of Dyssyntax in Semantic Networking
by Farshad Badie and Luis M. Augusto
AI 2022, 3(2), 353-370; https://doi.org/10.3390/ai3020022 - 20 Apr 2022
Cited by 1 | Viewed by 3906
Abstract
Formal thought disorder (FTD) is a clinical mental condition that is typically diagnosable by the speech productions of patients. However, this has been a vexing condition for the clinical community, as it is not at all easy to determine what “formal” means in [...] Read more.
Formal thought disorder (FTD) is a clinical mental condition that is typically diagnosable by the speech productions of patients. However, this has been a vexing condition for the clinical community, as it is not at all easy to determine what “formal” means in the plethora of symptoms exhibited. We present a logic-based model for the syntax–semantics interface in semantic networking that can not only explain, but also diagnose, FTD. Our model is based on description logic (DL), which is well known for its adequacy to model terminological knowledge. More specifically, we show how faulty logical form as defined in DL-based Conception Language (CL) impacts the semantic content of linguistic productions that are characteristic of FTD. We accordingly call this the dyssyntax model. Full article
(This article belongs to the Special Issue Conceptualization and Semantic Knowledge)
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