Toward truly intelligent information systems-from expert systems to automatic programming
TL;DR: A way of designing intelligent systems that assure autonomy, generality and practicality in problem solving to the greatest extent and can solve complex problems is discussed.
Abstract: The objective of this paper is to discuss a way of designing intelligent systems that assure autonomy, generality and practicality in problem solving to the greatest extent and can solve complex problems. There are various types of problem solving, depending on the object, and often more than one subjects concern the same problem with different roles in complex problem solving. In order to achieve our goal in this environment, a new architecture for the system and a new modeling scheme for representing problems including human activity are discussed, as well as a way of generating problem-specific problem solving systems. Several new concepts are included in this paper: a multi-level function structure and its corresponding knowledge structure, multiple meta-level operations, a multi-strata model to represent problems including human activity, etc. It is shown that the system realizes not only the generality but also the practicality of problem solving by enabling automatic programming.
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01 Jun 1998
TL;DR: It is shown that the system realizes not only the generality but also practicality of problem solving by enabling automatic programming.
Abstract: The objective of this paper is to discuss some aspects of large scale knowledge bases, especially the ways of building knowledge bases from the view point of using knowledge bases for solving real problems and for assuring knowledge based systems generality. A new modeling scheme for representing problems including strategic decision is discussed as well as a way of generating problem specific problem solving systems. Many multi-level concepts such as a multi-level function structure and its corresponding knowledge structure, multiple meta-level operations, a multi-strata model to represent problems including human activity, etc. It is shown that the system realizes not only the generality but also practicality of problem solving by enabling automatic programming.
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Cites methods from "Toward truly intelligent informatio..."
...The approach taken in this paper is to introduce a new multi-level concept so as to enable the system to make decisions dynamically on the way of problem solving [ 1 ]....
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22 Nov 1998
TL;DR: A new modeling scheme named multi-strata modeling is introduced as a key concept to make computer system intelligent.
Abstract: A formal way of modeling complex objects such as enterprises is discussed. Information system is indispensable in every enterprise to accomplish various activities required there and, therefore, must be defined as a part of an enterprise model. Programs of information systems are specified based on this model representation. It enables automation of the following programming process. A new modeling scheme named multi-strata modeling is introduced as a key concept to make computer system intelligent.
Proceedings Article•
09 Nov 1999
TL;DR: In this paper, the formal specification of language of knowledge processing system SKAUS (Super Knowledge Acquisition and Utilization System) which incorporates uncertain knowledge processing and non-symbolic information processing units in the system is provided.
Abstract: This paper is concerned with a preliminary consideration to provide the formal specification of language of knowledge processing system SKAUS (Super Knowledge Acquisition and Utilization System) which incorporates uncertain knowledge processing and non-symbolic information processing units in the system. SKAUS is planned as a super set of KAUS developed by the authors. KAUS implement multi-layer logic (MLL for short) based on classical set theory. SKAUS is intended to have additional capabilities of KAUS, such as representing uncertain knowledge in the forms of language used in fuzzy set theory and probability theory. In addition to this extension, we try to incorporate matrix logic into our extension so as to process non-symbolic information in corporation with neural networks.
Book•
01 Feb 2001
TL;DR: In this article, the types of integrations are defined by the relations between the different information processing methods to be integrated, and the most feasible way of integrating the different schemes is discussed.
Abstract: A way of integrating the different information processing methods is discussed. The types of integrations are defined by the relations between the different information processing methods to be integrated. By classifying these methods the type of integration is classified. This discussion reveals the most feasible way of integrating the different schemes. It is a sequence of integrating the methods via knowledge processing. Based on this discussion two important types of integrations are studied.
Journal Article•
TL;DR: In this paper, a formal way of modeling complex objects such as enterprises is discussed and a new modeling scheme named multi-strata modeling is introduced as a key concept to make computer system intelligent.
Abstract: A formal way of modeling complex objects such as enterprises is discussed. Information system is indispensable in every enterprise to accomplish various activities required there and, therefore, must be defined as a part of an enterprise model. Programs of information systems are specified based on this model representation. It enables automation of the following programming process. A new modeling scheme named multi-strata modeling is introduced as a key concept to make computer system intelligent.
References
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01 Jan 1988
TL;DR: This book describes the principles that guided the expert systems research group's work, looks in detail at the design and operation of each tool or methodology, and reports some lessons learned from the enterprise.
Abstract: In June of 1983, our expert systems research group at Carnegie Mellon University began to work actively on automating knowledge acquisition for expert systems. In the last five years, we have developed several tools under the pressure and influence of building expert systems for business and industry. These tools include the five described in chapters 2 through 6 - MORE, MOLE, SALT, KNACK and SIZZLE. One experiment, conducted jointly by developers at Digital Equipment Corporation, the Soar research group at Carnegie Mellon, and members of our group, explored automation of knowledge acquisition and code development for XCON (also known as R1), a production-level expert system for configuring DEC computer systems. This work influenced the development of RIME, a programming methodology developed at Digital which is the subject of chapter 7. This book describes the principles that guided our work, looks in detail at the design and operation of each tool or methodology, and reports some lessons learned from the enterprise. of the work, brought out in the introductory chapter, is A common theme that much power can be gained by understanding the roles that domain knowledge plays in problem solving. Each tool can exploit such an understanding because it focuses on a well defined problem-solving method used by the expert systems it builds. Each tool chapter describes the basic problem-solving method assumed by the tool and the leverage provided by committing to the method."
341 citations
02 Jan 1993
TL;DR: This chapter takes a few steps toward creating aTaxonomy of methods -- a taxonomy that identifies some of the discriminating characteristics of the methods expert systems use and that suggests how methods can be mapped onto tasks.
Abstract: Although efforts, some successful, to develop expert systems (application systems that can perform knowledge-intensive tasks) have been going on now for almost 20 years, we are not yet very good at describing the variations in problem-solving methods that these systems use, nor do we have much of an understanding of how to characterize the methods in terms of features of the types of tasks for which they are appropriate. This chapter takes a few steps toward creating a taxonomy of methods -- a taxonomy that identifies some of the discriminating characteristics of the methods expert systems use and that suggests how methods can be mapped onto tasks.
314 citations
01 Jun 1994
TL;DR: A system named AA1 (Articulation Aid 1) which aids human users in the formation of new concepts in the domain of engineering and science and is as nonprescriptive as possible, but gives stimulation for the user to form concepts that he could not by using only pencil and paper.
Abstract: This paper describes a system named AA1 (Articulation Aid 1) which aids human users in the formation of new concepts in the domain of engineering and science. From the viewpoint of concept formation, one main process of creation is divergent thinking in which broad alternatives are searched, and another process is convergent thinking in which a unique solution is sought. From the viewpoint of human activities, creation also includes the aspect of collaboration among people and the aspect of individual reflection, although they are interrelated. AA1, the system presented in this paper, supports divergent thinking during individual reflection. Engineers and scientists usually scrawl many notes on paper while exploring new possible concepts in the divergent thinking process. A system is needed to reflect the fragments of concepts that are not articulated yet and thereby stimulate the formation of new concepts. AA1 builds a two-dimensional space from the words the user provides. Looking at this space and other precedent spaces, the user can form new concepts little by little. The main feature of AA1 different, from existing hypermedia systems and CSCW systems is the strategy for building the space presented to the user. The system is as nonprescriptive as possible, but it gives stimulation for the user to form concepts that he could not by using only pencil and paper. Experimentation has shown that the space which AA1 displays can effectively help the user to build new concepts. The most prominent effect is that empty regions in the space automatically configured by the system often lead to new concepts. >
86 citations
TL;DR: A taxonomy for knowledge-acquisition aids that is based on the terms and relationships that a given tool uses to establish the semantics of a user's entries is described, which has important implications for how a knowledge- Acquisition tool is used and to what degree it can assist its users in analysing new applications at the knowledge level.
71 citations