Systemic Semiotics as a Basis for an Agent-Oriented Conceptual Modeling Methodology

2007 ◽  
pp. 256-286 ◽  
Author(s):  
Rodney J. Clarke ◽  
Aditya K. Ghose ◽  
Aneesh Krishna
Keyword(s):  
Systemic Functional Linguistics ◽  
Conceptual Modeling ◽  
Systems Development ◽  
Conceptual Modelling ◽  
Agent Based ◽  
Semiotic Model ◽  
Modeling Methodology ◽  
Service Organisation ◽  
Modelling Methodology ◽  
And Training

The authors demonstrate how Systemic Semiotics, an approach that combines a semiotic model of language called Systemic Functional Linguistics with selected concepts from Social Semiotics, can be applied to create Agent-Oriented Information Systems in which social processes can be elicited from stakeholders, specified by designers, and embedded into actual agent-based systems. The utility of Systemic Semiotics applied to Agent-Oriented Conceptual modelling is demonstrated by developing a real world system to address the problem of registering and training volunteers in an emergency service organisation. The experience of developing this system was then used to propose an experimental Agent-Oriented Conceptual Modelling Methodology that uses the same theory and concepts for describing the artefacts and the processes of agent-oriented systems development.

Impact of Service Organisation on Teaching and Training

2018 ◽  
pp. 211-237 ◽  
Author(s):  
Harry Kennedy ◽  
Luca Castelletti ◽  
Owen O’Sullivan
Keyword(s):  
Service Organisation ◽  
And Training

Using Ontology Languages for Conceptual Modeling

2012 ◽  
pp. 1-28
Author(s):  
Palash Bera ◽  
Anna Krasnoperova ◽  
Yair Wand
Keyword(s):  
Conceptual Models ◽  
Conceptual Modeling ◽  
Systems Development ◽  
Information Systems Development ◽  
Semantic Relationships ◽  
Support Domain ◽  
Domain Semantics ◽  
Ontology Languages ◽  
Conceptual Modeling Grammar ◽  
Precise Representation

Conceptual models are used to support understanding of and communication about application domains in information systems development. Such models are created using modeling grammars (usually employing graphic representation). To be effective, a grammar should support precise representation of domain concepts and their relationships. Ontology languages such as OWL emerged to define terminologies to support information sharing on the Web. These languages have features that enable representation of semantic relationships among domain concepts and of domain rules, not readily possible with extant conceptual modeling techniques. However, the emphasis in ontology languages has been on formalization and being computer-readable, not on how they can be used to convey domain semantics. Hence, it is unclear how they can be used as conceptual modeling grammars. We suggest using philosophically based ontological principles to guide the use of OWL as a conceptual modeling grammar. The paper presents specific guidelines for creating conceptual models in OWL and demonstrates, via example, the application of the guidelines to creating representations of domain phenomena. To test the effectiveness of the guidelines we conducted an empirical study comparing how well diagrams created with the guidelines support domain understanding in comparison to diagrams created without the guidelines. The results indicate that diagrams created with the guidelines led to better domain understanding of participants.

Using Agent Technology for Company Knowledge Management

2011 ◽  
pp. 1862-1879
Author(s):  
Victoria Yoon ◽  
Barbara Broome ◽  
Rahul Singh ◽  
Tor Guimaraes
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
System Approach ◽  
Systems Development ◽  
Decision Processes ◽  
Agent Technology ◽  
Agent Based ◽  
Complex Decision ◽  
A Company ◽  
Practical Implications

Emerging agent-based systems offer a new means of effectively managing knowledge to address complex decision processes, thereby enabling solutions to many real problems that have heretofore appeared intractable. This article presents an overview of expert system and agent technologies, and shows the latter as a powerful extension of artificial intelligence for systems development. To illustrate, a system developed first using an expert system approach and then an agent-based approach is used to identify the strengths and weaknesses of the agent-based approach. Last, the practical implications of a company adoption of agent-based technology for systems development are addressed.

scholarly journals Discussing the Use of Complexity Theory in Engineering Management: Implications for Sustainability

2020 ◽  
Vol 12 (24) ◽  
pp. 10629
Author(s):  
Gianpaolo Abatecola ◽  
Alberto Surace
Keyword(s):  
New Product Development ◽  
Complexity Theory ◽  
Conceptual Modeling ◽  
New Product ◽  
Engineering Management ◽  
Agent Based Modeling ◽  
Current Status ◽  
Future Research ◽  
Agent Based ◽  
Wide Range

What is the state-of-the-art literature regarding the adoption of the complexity theory (CT) in engineering management (EM)? What implications can be derived for future research and practices concerning sustainability issues? In this conceptual article, we critically discuss the current status of complexity research in EM. In this regard, we use IEEE Transactions on Engineering Management, because it is currently considered the leading journal in EM, and is as a reliable, heuristic proxy. From this journal, we analyze 38 representative publications on the topic published since 2000, and extrapolated through a rigorous keyword-based article search. In particular, we show that: (1) the adoption of CT has been associated with a wide range of key themes in EM, such as new product development, supply chain, and project management. (2) The adoption of CT has been witnessed in an increasing amount of publications, with a focus on conceptual modeling based on fuzzy logics, stochastic, or agent-based modeling prevailing. (3) Many key features of CT seem to be quite clearly observable in our dataset, with modeling and optimizing decision making, under uncertainty, as the dominant theme. However, only a limited number of studies appear to formally adhere to CT, to explain the different EM issues investigated. Thus, we derive various implications for EM research (concerning the research in and practice on sustainability issues).

Multi-Agent Based Dynamic E-Learning Environment

2011 ◽  
pp. 142-158 ◽  
Author(s):  
Saleh AlZahrani ◽  
Aladdin Ayesh ◽  
Hussein Zedan
Keyword(s):  
Learning Environment ◽  
Learning Objects ◽  
Agent Based ◽  
Development Framework ◽  
The World ◽  
E Learning ◽  
Multi Agent ◽  
The Subject ◽  
And Training ◽  
Agent Development

Grids are increasingly being used in applications, one of which is e-learning. As most of business and academic institutions (universities) and training centres around the world have adopted this technology in order to create, deliver and manage their learning materials through the Web, the subject has become the focus of investigate. Still, collaboration between these institutions and centres is limited. Existing technologies such as grid, Web services and agents are promising better results. In this article the authors support building our architecture Regionally Distributed Architecture for Dynamic e-Learning Environment (RDADeLE) by combining those technologies via Java Agent DEvelopment Framework (JADE). By describing these agents in details, they prove that agents can be implemented to work well to extend the autonomy and interoperability for learning objects as data grid.

Comparing Expert Systems and Agent Technology for KM

2011 ◽  
pp. 321-343
Author(s):  
Tor Guimaraes
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
System Approach ◽  
Systems Development ◽  
Decision Processes ◽  
Agent Technology ◽  
Agent Based ◽  
Complex Decision ◽  
A Company ◽  
Practical Implications

Agent technology offers a new means of effectively managing knowledge and addresses complex decision processes which heretofore appeared intractable. This chapter presents an overview and comparison of expert system and agent technologies, and shows the latter as a powerful extension in artificial intelligence for systems development. To illustrate, a system developed first using an expert system approach and then an agent-based approach are used to identify the strengths and weaknesses of the agent-based approach. Last, the practical implications of a company adoption of agent-based technology for systems development are addressed.

Evaluating Conceptual Modeling Practices

2011 ◽  
pp. 28-55
Author(s):  
Graeme Shanks ◽  
Jasmina Nuredini ◽  
Ron Weber
Keyword(s):  
Empirical Research ◽  
Real World ◽  
Theoretical Basis ◽  
Cognitive Process ◽  
Conceptual Modeling ◽  
Process Tracing ◽  
Conceptual Modelling ◽  
End User ◽  
Modeling Practices ◽  
Ontological Theory

This chapter examines how ontological theory can be used to predict how alternative conceptual modelling representations affect end-user understanding of these representations. Specifically, it examines how ontological theory can be used to show how part-whole relations (composites) and things and properties can be best represented to enhance understanding of these real-world phenomena. We report the outcomes of two experiments that provide evidence to support the ontologically sound representation of part-whole relations and things and properties. We also discuss the outcomes of a cognitive process tracing study that explains why the ontologically sound representation of things and properties is more easily understood. In essence, our empirical research provides evidence to support the use of ontology as a theoretical basis to guide conceptual modelling practices.

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