We outline an approach to building knowledge-based system based on tightly controlling the order of evaluation of the knowledge components of the system. The order of evaluation is based on two relations, sequence and correction that correspond to the changes that an expert may wish to make to a knowledge base and knowledge acquisition is structured so that new knowledge is added having one of these relations with existing knowledge in the system. We further propose that the knowledge components added might be any knowledge-based systems or programs rather than rules. This proposal is a generalisation of the Ripple-Down Rule incremental approach to building knowledge-based systems
Building a sizable knowledge base (KB) for an intelligent system is a non-trivial task. When users a...
Despite recent progress, knowledge acquisition remains a central problem for the development of inte...
In this paper we describe a system aimed at providing software support for the process of knowledge ...
We outline an approach to building knowledge-based system based on tightly controlling the order of ...
Incremental Knowledge Acquisition is an alternative approach to the ”established” knowledg...
In this work, we outline an approach to incrementally build-ing knowledge-based systems based on tig...
Codifying expert domain knowledge is a difficult and expensive task. To evaluate the quality of the ...
: Incremental refinement methods of knowledge bases ease maintenance but fail to uncover the underly...
The aim of this study was to develop machine learning techniques that would facilitate knowledge acq...
. We present an assistance tool for the incremental construction of knowledge bases. First it divide...
Knowledge Acquisition refers to the transfer of expertise from a human expert into a knowledge-base ...
In this paper we present the outline of a method that combines a divide-and-conquer approach, that i...
This paper presents a learning-based approach to the automation of knowledge acquisition for expert ...
Modifying knowledge-based systems (KBSs) is a complex activity. One of its di-culties is that severa...
Ripple Down Rules (RDR) is a maturing collection of methodologies for the incremental development an...
Building a sizable knowledge base (KB) for an intelligent system is a non-trivial task. When users a...
Despite recent progress, knowledge acquisition remains a central problem for the development of inte...
In this paper we describe a system aimed at providing software support for the process of knowledge ...
We outline an approach to building knowledge-based system based on tightly controlling the order of ...
Incremental Knowledge Acquisition is an alternative approach to the ”established” knowledg...
In this work, we outline an approach to incrementally build-ing knowledge-based systems based on tig...
Codifying expert domain knowledge is a difficult and expensive task. To evaluate the quality of the ...
: Incremental refinement methods of knowledge bases ease maintenance but fail to uncover the underly...
The aim of this study was to develop machine learning techniques that would facilitate knowledge acq...
. We present an assistance tool for the incremental construction of knowledge bases. First it divide...
Knowledge Acquisition refers to the transfer of expertise from a human expert into a knowledge-base ...
In this paper we present the outline of a method that combines a divide-and-conquer approach, that i...
This paper presents a learning-based approach to the automation of knowledge acquisition for expert ...
Modifying knowledge-based systems (KBSs) is a complex activity. One of its di-culties is that severa...
Ripple Down Rules (RDR) is a maturing collection of methodologies for the incremental development an...
Building a sizable knowledge base (KB) for an intelligent system is a non-trivial task. When users a...
Despite recent progress, knowledge acquisition remains a central problem for the development of inte...
In this paper we describe a system aimed at providing software support for the process of knowledge ...