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Decision-Making in Conceptual Design


In a nutshell, iConceptStore is an application back-end development toolkit, based on a dynamic conceptually structured information store (modelbase) with inter-related information and code components and declarative conceptual modelling language (CML). It is both connectible and user-extensible.

The following expressions reflect other aspects (alternative views) of iConceptStore:


Expert Knowledge Representation and Management System


Dynamic Application Domain Conceptual Modelling Environment


Application Infrastructure and Control-Flow Management System


Universal Algebraic Computing Framework


Intelligent Information Integrator-Organiser, providing uniform aggregated/consolidated object view and (both interactive and programmatic) access to conceptually related information items anywhere in any form – possibly dispersed among iConceptStore native modelbases and conventional SQL databases as well as different types of files on the local machine and/or the LAN and/or the Internet.

Most of the specialised knowledge, which experts use in their professional activities, is a product of generalisation of the common positive and negative experiences of many people over long periods of time. Although subjective by inception, through the process of gradual accumulation and scientific generalisation and refinement this knowledge has become shared public resource of the mankind as a whole and can not be ignored. While it may progressively change, it is relatively stable in nature. Individuals typically acquire such expert knowledge by means of different forms of education and practical training as well as through individual study. This way, the acquired parts of knowledge become individualised again but in an extensively augmented and refined form. More importantly, these parts of knowledge are not obtained in isolation but in close conjunction with the remaining virtual body of shared public knowledge thus serving as access points for consulting relevant parts of it as needed. Interdisciplinary teams provide additional means of knowledge consolidation on the spot by combining diverse knowledge fragments for the purpose of specific problem-solving efforts. Indeed, the need of dynamic knowledge consolidation becomes more pronounced. In their professional lives people rarely rely exclusively on their personal findings, obtained through observation and assessment of the results of their actions in the environment.

Although individual experts may contribute to the incremental extension and improvement of this body of knowledge, their direct role in knowledge acquisition and refinement as a whole is limited. In  most cases personal experiences can only serve to validate small parts of it. However, the work of individual experts can influence knowledge acquisition indirectly. In addition to the explicit knowledge, contained in books and other professional literature, the practical solutions - products of such professional activities - implicitly embody some expertise and can themselves be considered as sources of specialised knowledge, which needs to be extracted, generalised and represented in an explicit form in order to become usable by other people and/or systems. Indeed, the main purpose of science, engineering and economics research is producing such generalised knowledge, which could span many different fields of human expertise and is intended for use by other people.

If human intellectual abilities, especially in creative professional contexts, are so profoundly dependent on such specialised in scope (though generalised by formation) knowledge, then even partial automation of those activities with any related decision support would require incorporation of parts of that sharable knowledge within the corresponding software and information systems. This is especially true for such areas as engineering, manufacturing, investment and business and economics in general.

Since the body of expert knowledge (accumulated and potentially obtainable) is huge and diverse, powerful technologies (languages, techniques and tools) are needed for its selective elicitation, systematisation, representation and maintenance in persistent and usable digital form. The main role of the iConceptStore Conceptor knowledge engineering subsystem is to serve as such a knowledge acquisition and management tool for describing mental representations of selected fragments of the advanced problem-solving, planning and decision making methodology in the form of domain conceptual models, subsequently generating, maintaining and providing access to their digital images in lieu of expert knowledge bases. In turn, those models can possibly serve as relatively stable domains of interpretation for other levels of dynamic intelligence (reasoning).

Historically, our idea of separating at different levels the logic based reasoning from its conceptually represented domain model was conceived in the early 80’s while working on extending the language and functionality of a particular Prolog system, the results first published in 1986 as a rudimentary provision of explicit interpretation for that semantically extended logic programming system. The integration of this kind of domain conceptual modelling, commencing an independent existence with the inception of iConceptStore in 2001, with a suitable logic programming system (preferably Prolog) still seems a potentially beneficial way of complementing the expressive power and related functionality of its knowledge level cognitive architecture, to borrow the term (and spirit) from the title of the seminal 1980 AAAI Presidential Address and related later paper "The Knowledge Level" by Allen Newell:


Since Observer and Effector can not be really general purpose components, iConceptStore infrastructure only provides linkage to such gears in the form of Perception and Recipient standard CML ties to be attached to corresponding custom-supplied EntityNet server-side extensions, the latter serving as a kind of specific sensor and actuator driver routines, respectively. Therefore, the next picture has those minimalist components moved to the background in order to emphasize the essential parts of the iConceptStore cognitive architecture:


The Reasoning component per se is no longer meant to be a separate logic programming based external module. Instead, it now leverages the iConceptStore new built-in Inference, Rule and Event based deductive mechanisms, combining the logic of dynamic micro-planning with selective execution through close integration with the iConceptStore executive environment, performing the actual processes/actions as planned. The iConceptStore flexible representation of information allows programmatic altering of the internal logic of these components on-the-fly thus adapting to any dynamic changes in the current problem situation.

Note that although iConceptStore comes with some utilities for interactive access to its modelbases, generally it is meant to serve as an application back-end development toolset and no extensive user front-end facilities are currently available apart from the Conceptor CML Compiler and those interactive utilities. Again, flexible APIs are provided in order to facilitate development of such specific user-interface software components by partners and/or customers alike.

The main goal behind iConceptStore is to provide inovative application infrastructure and related toolset, supporting an original evolutional vision for advanced application development in the mainstream computing. Its cognitive architecture (knowledge bearing structures and mechanisms) is geared towards providing CML feeds of expert knowledge to application systems (as means of knowledge acquisition in lieu of “professional training”) thus supporting expert problem-solving and decision-making, based on deep understanding through comprehensive analysis of problem situations. For this purpose it deploys a set of consistent technologies, uniquely implementing and integrating advanced ideas and techniques from different research areas of computer science (including our own original contributions) in complience with good current development trends and practices with no exotic programming languages and environments involved.

Although iConceptStore provides a number of optional system modelling categories and related infrastructure and mechanisms to encourage and assist a more systematic approach, it does not impose or promote any particular paradigm or formalism or style of modelling apart from applying common sense. Rather, it is designed to be universally applicable by supporting the expression of any modelling conceptualisation possibly conceived, allowing users to describe any target domain of expertise in their preferred natural terms and style, most appropriate for the specific task at hand and degree of detail at a particular stage of modelling. In fact, any Conceptor CML entity can be used as a convenient medium for wrapping any information structure and related functionality under unique identity, thus providing for its easy inclusion into and linkage to other structures.

Currently running under MS Windows XP/7/10 Professional as well as Windows Server 2008 and later (32-/64-bit) operating systems, iConceptStore is integrated with MS Office, Internet Explorer, SQL Server and other MS tools and is further extensible by means of custom functions to provide for user specific modelling capabilities. Its well structured framework is intended for predominantly programmatic use. Hence, it can easily embed (or connect to) other software and information components and/or be embedded within (or connected to) any other software system. As a typical example, iConceptStore can serve as an intelligent back-end companion to MS Excel, greatly enriching its modelling capabilities in a very natural way.


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