Some philosophic foundations for an environment for system building (original) (raw)

Development of a Conceptual Model for Intelligent Software System Designing

Review of information engineering and applications, 2022

This article provides information on the design of intelligent software systems. An intelligent software system refers to any software using artificial intelligence to analyze and interpret data or to communicate with systems and people. The article substantiates the relevance of the issue and highlights existing problems. The following factors are taken into consideration when assessing the problems of intelligent software system designing: easy data collection, low cost of developing intelligent systems, availability of experts and necessary resources (computers, program developers, software, etc.). The article also reports of related studies and identifies application areas. A conceptual model is developed for the design of intelligent software systems. The stages, components, directions, etc. indicated in the conceptual model for the design of intelligent software systems are studied and the characteristics of each are determined. Some examples of design types by the fields of activity are identified. The developed model can be used in the design of intelligent software systems related to any instrumental programming. Contribution/Originality: A conceptual model is developed for the design of intelligent software systems. The stages, components, directions, etc. indicated in the conceptual model for the design of intelligent software systems are studied and the characteristics of each are determined. type of personality, i.e., a person belonging to the cyber world, is formed being affected by intelligent systems [2]. Intelligent systems also suffer from the security issues of a person's private life and provision of data security. Based

An integrated methodology for knowledge-based system development

Expert Systems with Applications, 1994

This article details a rigorous development methodology for knowledge-based systems. This rigorous methodology is itself embedded within a multilevel process model for software development. The rigorous methodology is designed to utilize a set of formal or rigorous specifications in a composite style. These specifications detail areas like the knowledge base, the human-computer interface, and the representation, linked together through a process of representation refinement. The rigorous methodology aims at combining the aspects of knowledge engineering, cognitive engineering, and software engineering as they relate to knowledge-based systems. The knowledge-based systems development methodology is embedded within a two-level life, cycle model. The two levels are termed the macroand microlevels. The macrolevel is used to understand the impact that those factors external to the actual system development have upon the system's creation and life cycle. These external factors include such influences as changes in technology and corporate planning. The microlevel is a process model that utilizes techniques.from total quality management, measurement theory, and cost estimation, among others, to assist the software developer in producing software through a process of never-ending quality improvement. All of these techniques are utilized and complimentary to each other. The aim of having two levels is to allow the developer to focus upon each item separately but to understand the factors upon which the factor's development rests and its impact upon the other subprocesses.

Design environments for intelligent systems

2002

There is a need to balance the quality of professionally designed information systems with the end user's current knowledge of specific decision contexts. This is particularly so for intelligent systems. This paper looks at some theoretical underpinnings for the potential enduser development of intelligent systems. General requirements are characterised and the metaphor of a semantic spreadsheet is introduced. A two level process enabling end user development of knowledge-based systems is described. The first involves the development of a design environment that allows experts to develop the knowledge base. The second involves development within the design environment for the ultimate end users.

A framework for application systems engineering

Information Systems, 1985

Interactive Application Systems (IAS) attend to the information needs of application experts, i.e. problem-solving end-users within particular application environments. As such. IAS must be customized functionally and behaviourally toward both user and environment. Such customizing must be feasible in an economical fashion. The study claims that this objective is met by appropriate IAS development tools and by a basic IAS architecture that consists of the following main building blocks: a general-purpose dialogue processor that is controlled by a particular user interface specification, called information net; a library of software modules and packages for providing system functions on the basis of reusable software; and a data management system that may, just like the library elements, be procured from outside, perhaps even including an already existing information base. The paper discusses the approach in detail with particular emphasis on information nets and on the integration of reusable software into a total system. The paper argues that the approach is flexible enough to accommodate (rapid) prototyping, i.e. procuring of first versions of an IAS, that may be used during requirements analysis to refine the user wishes, or operationally during an interim period until the final system becomes available.

An Architectural Approach to Cognitive Information Systems

Acta Polytechnica Hungarica, 2020

The fast changes in information technology and business needs have led to the evolution and development of Cognitive Information Systems (CIS). There have been few pieces of research on the general model for the analysis and design of CIS. This paper attempts to create a design scheme for incorporating the various models for CISs and Understanding-based management systems (UBMSS). The components that have been examined, create elements of CIS analysis and design, however, they were not described as modeling elements and not described as enabling tools needed to create a consistent and integrated system. The most significant components for modeling are: semi-structured documents, business processes, constituents of knowledge management, the enterprise and the information architecture, including self-directing software components-Artificial Intelligence (AI)-that yield functions. For CIS modeling, the above-mentioned elements were combined into a unified framework, that follows the object-oriented paradigm and architecture approach. The aim of the research is to describe a framework that presents an overarching model and assists our understanding of the properties of CIS and UBMSS, allowing the formulation of a practical development method for CIS and cognitive management systems.

The Knowledge Level Approach To Intelligent Information System Design

2003

Traditional approaches to building intelligent information systems employ an ontology to define a representational structure for the data and information of interest within the target domain of the system. At runtime, the ontology provides a constrained template for the creation of the individual objects and relationships that together define the state of the system at a given point in time. The ontology also provides a vocabulary for expressing domain knowledge typically in the form of rules (declarative knowledge) or methods (procedural knowledge). The system utilizes the encoded knowledge, often in conjunction user input, to progress the state of the system towards the specific goals indicated by the users. While this approach has been very successful, it has some drawbacks. Regardless of the implementation paradigm the knowledge is essentially buried in the code and therefore inaccessible to most domain experts. The knowledge also tends to be very domain specific and is not exte...

Developing knowledge-based systems with MIKE

… Software Engineering, 1998

The paper describes the MIKE (Model-based and Incremental Knowledge Engineering) approach for developing knowledge-based systems. MIKE integrates semiformal and formal specification techniques together with prototyping into a coherent framework. All activities in the building process of a knowledge-based system are embedded in a cyclic process model. For the semiformal representation we use a hypermedia-based formalism which serves as a communication basis between expert and knowledge engineer during knowledge acquisition. The semiformal knowledge representation is also the basis for formalization, resulting in a formal and executable model specified in the Knowledge Acquisition and Representation Language (KARL). Since KARL is executable, the model of expertise can be developed and validated by prototyping. A smooth transition from a semiformal to a formal specification and further on to design is achieved because all the description techniques rely on the same conceptual model to describe the functional and nonfunctional aspects of the system. Thus, the system is thoroughly documented at different description levels, each of which focuses on a distinct aspect of the entire development effort. Traceability of requirements is supported by linking the different models to each other.

The systematic construction of information systems

2000

Process modelling is a vital issue for communicating with experts of the application domain. Depending on the roles and responsibilities of the application domain experts involved, process models are discussed on different levels of abstraction. These may range from detailed regulation for process execution to the interrelation of basic core processes on a strategic level.