The Language of General Systems Logical Theory (Gslt)

Resconi, Germano; Rattray, Charles; Hill, Gillian

doi:10.1080/03081079908935244

Cited by 12 publications

(5 citation statements)

References 8 publications

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“…The approach of Mesarović and Takahara (1975, 1989) is the basis for several developments, such as the development towards the concepts of system transformation and adaptive systems by Saito (1999). Also, the language of general systems logical theory (GSLT) (Resconi et al ., 1999) refers to Mesarović and Takahara; GSLT is based on their input–output concept and is expressed by means of category theory concepts. The language of the more formal and general GSLT is said to be complementary to and has the same aim as the more problem‐solving oriented general systems problem solver (GSPS) of Klir (1985).…”

Section: Detailed Accounts Of Gst Use In Articles From 1995 To 2006mentioning

confidence: 99%

Recent developments in general system theory

Drack

Schwarz

2010

Syst. Res.

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Bertalanffy's general system theory (GST) was conceived as a unifying research program, as a science of ‘wholeness’ to overcome or complement mechanistic and reductionist approaches. More than 50 years since the founding of the Society for General Systems Research (SGSR), today's International Society for the Systems Sciences (ISSS), two questions arise about the developments in GST research. Are there recent contributions towards enhancing GST? Are there simplifications compared to Bertalanffy's original program? To answer these questions we analysed in detail 161 articles in peer reviewed journals that referred to GST and appeared between 1995 and 2006. We emphasized contributions made in science and philosophy. Even though the system approach was introduced in applied fields such as engineering and management, we did not include these fields in this article. Copyright © 2010 John Wiley & Sons, Ltd.

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Section: Detailed Accounts Of Gst Use In Articles From 1995 To 2006mentioning

confidence: 99%

Recent developments in general system theory

Drack

Schwarz

2010

Syst. Res.

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“…In the RLR we have used category theory formalism, along with general systems logical theory (GSLT) [ 38 ], to formalize agents' communications. For instance, the communication between different semantic unities [ 14 ] can be represented as in Figure 13 .…”

Section: Employing Category Theory In the Rlr Frameworkmentioning

confidence: 99%

Managing Requirement Volatility in an Ontology-Driven Clinical LIMS Using Category Theory

Shaban-Nejad

Ormandjieva

Kassab

et al. 2009

International Journal of Telemedicine and Applications

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Requirement volatility is an issue in software engineering in general, and in Web-based clinical applications in particular, which often originates from an incomplete knowledge of the domain of interest. With advances in the health science, many features and functionalities need to be added to, or removed from, existing software applications in the biomedical domain. At the same time, the increasing complexity of biomedical systems makes them more difficult to understand, and consequently it is more difficult to define their requirements, which contributes considerably to their volatility. In this paper, we present a novel agent-based approach for analyzing and managing volatile and dynamic requirements in an ontology-driven laboratory information management system (LIMS) designed for Web-based case reporting in medical mycology. The proposed framework is empowered with ontologies and formalized using category theory to provide a deep and common understanding of the functional and nonfunctional requirement hierarchies and their interrelations, and to trace the effects of a change on the conceptual framework.

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“…Dubois and Prade [11] explored three main semantics for membership functions in which each semantics underlies a particular class of applications. Resconi et al developed a hierarchical uncertainty meta-theory based upon modal logic [2][3][4][5][6][7][8][9]. At the same time, Gebhardt and Kruse [12] developed a model for vagueness and uncertainty called the context model that provides a formal framework for the comparison and semantic foundation of several theories of uncertainty.…”

Section: Introductionmentioning

confidence: 98%

“…In a broader sense, it is used to involve the interdisciplinary field of research concerned with the search for methods of modelling uncertain knowledge. Those methods can refer to any application domain and any level of knowledge: one seeks ways of representing both object-level knowledge and meta-level knowledge, the latter being the knowledge necessary to reason about the former [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%