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Article
Publication date: 31 August 2004

Helmut Meisel and Ernesto Compatangelo

This paper describes an architecture for the usage of Instructional Design (ID) knowledge in intelligent instructional systems. In contrast with other architectures…

Abstract

This paper describes an architecture for the usage of Instructional Design (ID) knowledge in intelligent instructional systems. In contrast with other architectures, ontologies are used to represent ID knowledge about both what to teach and how to teach. Moreover, set‐theoretic reasoning is used for the provision of inferential services. In particular, the paper shows how set‐theoretic deductions can be applied (i) to support the modelling of ID knowledge bases, (ii) to retrieve suitable teaching methods from them, and (iii) to detect errors in a training design. The intelligent knowledge management environment CONCEPTOOL is used to demonstrate the benefits of the proposed architecture.

Details

Interactive Technology and Smart Education, vol. 1 no. 3
Type: Research Article
ISSN: 1741-5659

Keywords

Article
Publication date: 1 January 2006

Rob Miller

The purpose of this article is to give a non‐technical overview of some of the technical progress made recently on tackling three fundamental problems in the area of…

760

Abstract

Purpose

The purpose of this article is to give a non‐technical overview of some of the technical progress made recently on tackling three fundamental problems in the area of formal knowledge representation/artificial intelligence. These are the Frame Problem, the Ramification Problem, and the Qualification Problem. The article aims to describe the development of two logic‐based languages, the Event Calculus and Modular‐E, to address various aspects of these issues. The article also aims to set this work in the wider context of contemporary developments in applied logic, non‐monotonic reasoning and formal theories of common sense.

Design/methodology/approach

The study applies symbolic logic to model aspects of human knowledge and reasoning.

Findings

The article finds that there are fundamental interdependencies between the three problems mentioned above. The conceptual framework shared by the Event Calculus and Modular‐E is appropriate for providing principled solutions to them.

Originality/value

This article provides an overview of an important approach to dealing with three fundamental issues in artificial intelligence.

Details

Aslib Proceedings, vol. 58 no. 1/2
Type: Research Article
ISSN: 0001-253X

Keywords

Article
Publication date: 18 June 2021

Karsten Winther Johansen, Rasmus Nielsen, Carl Schultz and Jochen Teizer

Real-time location sensing (RTLS) systems offer a significant potential to advance the management of construction processes by potentially providing real-time access to…

Abstract

Purpose

Real-time location sensing (RTLS) systems offer a significant potential to advance the management of construction processes by potentially providing real-time access to the locations of workers and equipment. Many location-sensing technologies tend to perform poorly for indoor work environments and generate large data sets that are somewhat difficult to process in a meaningful way. Unfortunately, little is still known regarding the practical benefits of converting raw worker tracking data into meaningful information about construction project progress, effectively impeding widespread adoption in construction.

Design/methodology/approach

The presented framework is designed to automate as many steps as possible, aiming to avoid manual procedures that significantly increase the time between progress estimation updates. The authors apply simple location tracking sensor data that does not require personal handling, to ensure continuous data acquisition. They use a generic and non-site-specific knowledge base (KB) created through domain expert interviews. The sensor data and KB are analyzed in an abductive reasoning framework implemented in Answer Set Programming (extended to support spatial and temporal reasoning), a logic programming paradigm developed within the artificial intelligence domain.

Findings

This work demonstrates how abductive reasoning can be applied to automatically generate rich and qualitative information about activities that have been carried out on a construction site. These activities are subsequently used for reasoning about the progress of the construction project. Our framework delivers an upper bound on project progress (“optimistic estimates”) within a practical amount of time, in the order of seconds. The target user group is construction management by providing project planning decision support.

Research limitations/implications

The KB developed for this early-stage research does not encapsulate an exhaustive body of domain expert knowledge. Instead, it consists of excerpts of activities in the analyzed construction site. The KB is developed to be non-site-specific, but it is not validated as the performed experiments were carried out on one single construction site.

Practical implications

The presented work enables automated processing of simple location tracking sensor data, which provides construction management with detailed insight into construction site progress without performing labor-intensive procedures common nowadays.

Originality/value

While automated progress estimation and activity recognition in construction have been studied for some time, the authors approach it differently. Instead of expensive equipment, manually acquired, information-rich sensor data, the authors apply simple data, domain knowledge and a logical reasoning system for which the results are promising.

Article
Publication date: 10 June 2021

Xia Zhang, Youchao Sun and Yanjun Zhang

Semantic modelling is an essential prerequisite for designing the intelligent human–computer interaction in future aircraft cockpit. The purpose of this paper is to…

Abstract

Purpose

Semantic modelling is an essential prerequisite for designing the intelligent human–computer interaction in future aircraft cockpit. The purpose of this paper is to outline an ontology-based solution to this issue.

Design/methodology/approach

The scenario elements are defined considering the cognitive behaviours, system functions, interaction behaviours and interaction situation. The knowledge model consists of a five-tuple array including concepts, relations, functions, axioms and instances. Using the theory of belief-desire-intention, the meta-model of cognitive behaviours is established. The meta-model of system functions is formed under the architecture of sub-functions. Supported by information flows, the meta-model of interaction behaviours is presented. Based on the socio-technical characteristics, the meta-model of interaction situation is proposed. The knowledge representation and reasoning process is visualized with the semantic web rule language (SWRL) on the Protégé platform. Finally, verification and evaluation are carried out to assess the rationality and quality of the ontology model. Application scenarios of the proposed modelling method are also illustrated.

Findings

Verification results show that the knowledge reasoning based on SWRL rules can further enrich the knowledge base in terms of instance attributes and thereby improve the adaptability and learning ability of the ontology model in different simulations. Evaluation results show that the ontology model has a good quality with high cohesion and low coupling.

Practical implications

The approach presented in this paper can be applied to model complex human–machine–environment systems, from a semantics-driven perspective, especially for designing future cockpits.

Originality/value

Different from the traditional approaches, the method proposed in this paper tries to deal with the socio-technical modelling issues concerning multidimensional information semantics. Meanwhile, the constructed model has the ability of autonomous reasoning to adapt to complex situations.

Details

Aircraft Engineering and Aerospace Technology, vol. 93 no. 5
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 15 August 2016

Behzad Bayat, Julita Bermejo-Alonso, Joel Carbonera, Tullio Facchinetti, Sandro Fiorini, Paulo Goncalves, Vitor A.M. Jorge, Maki Habib, Alaa Khamis, Kamilo Melo, Bao Nguyen, Joanna Isabelle Olszewska, Liam Paull, Edson Prestes, Veera Ragavan, Sajad Saeedi, Ricardo Sanz, Mae Seto, Bruce Spencer, Amirkhosro Vosughi and Howard Li

IEEE Ontologies for Robotics and Automation Working Group were divided into subgroups that were in charge of studying industrial robotics, service robotics and autonomous…

Abstract

Purpose

IEEE Ontologies for Robotics and Automation Working Group were divided into subgroups that were in charge of studying industrial robotics, service robotics and autonomous robotics. This paper aims to present the work in-progress developed by the autonomous robotics (AuR) subgroup. This group aims to extend the core ontology for robotics and automation to represent more specific concepts and axioms that are commonly used in autonomous robots.

Design/methodology/approach

For autonomous robots, various concepts for aerial robots, underwater robots and ground robots are described. Components of an autonomous system are defined, such as robotic platforms, actuators, sensors, control, state estimation, path planning, perception and decision-making.

Findings

AuR has identified the core concepts and domains needed to create an ontology for autonomous robots.

Practical implications

AuR targets to create a standard ontology to represent the knowledge and reasoning needed to create autonomous systems that comprise robots that can operate in the air, ground and underwater environments. The concepts in the developed ontology will endow a robot with autonomy, that is, endow robots with the ability to perform desired tasks in unstructured environments without continuous explicit human guidance.

Originality/value

Creating a standard for knowledge representation and reasoning in autonomous robotics will have a significant impact on all R&A domains, such as on the knowledge transmission among agents, including autonomous robots and humans. This tends to facilitate the communication among them and also provide reasoning capabilities involving the knowledge of all elements using the ontology. This will result in improved autonomy of autonomous systems. The autonomy will have considerable impact on how robots interact with humans. As a result, the use of robots will further benefit our society. Many tedious tasks that currently can only be performed by humans will be performed by robots, which will further improve the quality of life. To the best of the authors’knowledge, AuR is the first group that adopts a systematic approach to develop ontologies consisting of specific concepts and axioms that are commonly used in autonomous robots.

Details

Industrial Robot: An International Journal, vol. 43 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Book part
Publication date: 10 July 2019

Tianxing Wu, Guilin Qi and Cheng Li

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and

Abstract

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. Besides, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management, and so on. In recent years, knowledge graph techniques in China are also developing rapidly and different Chinese knowledge graphs have been built to support various applications. Under the background of “One Belt One Road (OBOR)” initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China on developing knowledge graph is also a good reference. Thus, in this chapter, the authors mainly introduce the development of Chinese knowledge graphs and their applications. The authors first describe the background of OBOR, and then introduce the concept of knowledge graph and three typical Chinese knowledge graphs, including Zhishi.me, CN-DBpedia, and XLORE. Finally, the authors demonstrate several applications of Chinese knowledge graphs.

Details

The New Silk Road Leads through the Arab Peninsula: Mastering Global Business and Innovation
Type: Book
ISBN: 978-1-78756-680-4

Keywords

Article
Publication date: 2 March 2015

Ahmad Shawan, Jean-Claude Léon, Gilles Foucault and Lionel Fine

Preparing digital mock-ups (DMUs) for finite element analyses (FEAs) is currently a long and tedious task requiring many interactive CAD model transformations. Functional…

Abstract

Purpose

Preparing digital mock-ups (DMUs) for finite element analyses (FEAs) is currently a long and tedious task requiring many interactive CAD model transformations. Functional information about components appears to be very useful to speed this preparation process. The purpose of this paper is to shows how DMU components can be automatically enriched with some functional information.

Design/methodology/approach

DMUs are widespread and stand as reference model for product description. However, DMUs produced by industrial CAD systems essentially contain geometric models, which lead to tedious preparation of finite element Models (FEMs). Analysis and reasoning approaches are developed to automatically enrich DMUs with functional and kinematic properties. Indeed, geometric interfaces between components form a key starting point to analyze their behaviors under reference states. This is a first stage in a reasoning process to progressively identify mechanical, kinematic as well as functional properties of components.

Findings

Inferred semantics adds up to the pure geometric representation provided by a DMU and produce also geometrically structured components. Functional information connected to a structured geometric model of a component significantly improves FEM preparation and increases its robustness because idealizations can take place using components’ functions and components’ structure helps defining sub-domains of FEMs.

Research limitations/implications

Future research will carry on improving algorithms for geometric interfaces identification, processing a wider range of component functions, which will contribute to a formalization of the concept of functional consistency of a DMU.

Originality/value

Simulation engineers benefit from this automated enrichment of DMUs with functional information to speed up the preparation of FEAs of large assemblies.

Details

Engineering Computations, vol. 32 no. 1
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 8 January 2018

Haihua Zhu and Jing Li

Three-dimensional digital design and manufacturing technology are changing the current manufacturing pattern and have become the core of enterprise competition. However…

Abstract

Purpose

Three-dimensional digital design and manufacturing technology are changing the current manufacturing pattern and have become the core of enterprise competition. However, the research and application of three-dimensional digital technology in the present phase have a strong bias toward the design of three-dimensional model and focus little on process planning. It restricts the development of manufacturing industry. Therefore, this paper aims to present a design scheme of three-dimensional digital process planning.

Design/methodology/approach

A three-dimensional digital process design method is developed by combining model-based definition technology and knowledge engineering technology. Model-based definition technology is used to display the process information. And knowledge engineering technology is used for process decision; meanwhile, ontology technology is introduced to describe process knowledge. And taking shaft part as an example, this paper establishes the general ontology of manufacturing process and the special ontology of shaft. This research provides an available method for the three-dimensional digital process planning.

Findings

Traditional process planning mainly is based on two-dimensional engineering drawing, which leads to the low efficiency and quality of process planning. Moreover, it cannot achieve effective mining and management of knowledge. Thus, applying an effective knowledge management technology into a three-dimensional process system is necessary.

Research limitations/implications

This paper contributes to an available method for three-dimensional digital process planning.

Originality/value

The introduction of model-based definition technology makes process information display in three-dimensional environment. And ontology technology achieves sematic reference and efficient management of process knowledge.

Details

Kybernetes, vol. 47 no. 4
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 29 March 2011

Kumar S. Ray and Arpan Chakraborty

The importance of fuzzy logic (FL) in approximate reasoning, and that of default logic (DL) in reasoning with incomplete information, is well established. Also, the need…

Abstract

Purpose

The importance of fuzzy logic (FL) in approximate reasoning, and that of default logic (DL) in reasoning with incomplete information, is well established. Also, the need for a commonsense reasoning framework that handles both these aspects has been widely anticipated. The purpose of this paper is to show that fuzzyfied default logic (FDL) is an attempt at creating such a framework.

Design/methodology/approach

The basic syntax, semantics, unique characteristics and examples of its complex reasoning abilities have been presented in this paper.

Findings

Interestingly, FDL turns out to be a generalization of traditional DL, with even better support for non‐monotonic reasoning.

Originality/value

The paper presents a generalized tool for commonsense reasoning which can be used for inference under incomplete information.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 4 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 20 August 2018

Karen Wickett

The purpose of this paper is to present a framework for the articulation of relationships between collection-level and item-level metadata as logical inference rules. The…

Abstract

Purpose

The purpose of this paper is to present a framework for the articulation of relationships between collection-level and item-level metadata as logical inference rules. The framework is intended to allow the systematic generation of relevant propagation rules and to enable the assessment of those rules for particular contexts and the translation of rules into algorithmic processes.

Design/methodology/approach

The framework was developed using first order predicate logic. Relationships between collection-level and item-level description are expressed as propagation rules – inference rules where the properties of one entity entail conclusions about another entity in virtue of a particular relationship those individuals bear to each other. Propagation rules for reasoning between the collection and item level are grouped together in the framework according to their logical form as determined by the nature of the propagation action and the attributes involved in the rule.

Findings

The primary findings are the analysis of relationships between collection-level and item-level metadata, and the framework of categories of propagation rules. In order to fully develop the framework, the paper includes an analysis of colloquial metadata records and the collection membership relation that provides a general method for the translation of metadata records into formal knowledge representation languages.

Originality/value

The method for formalizing metadata records described in the paper represents significant progress in the application of knowledge representation techniques to problems of metadata creation and management, providing a flexible technique for encoding colloquial metadata as a set of statements in first-order logic. The framework of rules for collection/item metadata relationships has a range of potential applications for the enhancement or metadata systems and vocabularies.

Details

Journal of Documentation, vol. 74 no. 6
Type: Research Article
ISSN: 0022-0418

Keywords

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