The current paradigm of modelling uncertainty in expert systems knowledge bases using Certainty Factors (CF) has been critically evaluated. A way to circumvent the awkwardness, non-intuitiveness and constraints encountered while using CF has been proposed. It is based on introducing Data Marks for askable conditions and Data Marks for conclusions of relational models, followed by choosing the best suited way to propagate those Data Marks into Data Marks of rule conclusions. This is done in a way orthogonal to the inference using Aristotelian Logic. Using Data Marks instead of Certainty Factors removes thus the intellectual discomfort caused by rejecting the notion of truth, falsehood and the Aristotelian law of excluded middle, as is done w...
The quality of an expert system, it is argued in this paper, is determined by the quality of its kno...
AbstractMost expert knowledge is ill-defined and heuristic. Therefore, many present-day rule-based e...
AbstractThis paper compares four measures that have been advocated as models for uncertainty in expe...
The current paradigm of modelling uncertainty in expert systems knowledge bases using Certainty Fact...
A way to circumvent the awkwardness and constraints encountered while using Certainty Factors (CF) f...
This paper presents an approach to the explicit integration of uncertain reasoning mechanisms into ...
Although the first rule-based systems were created as early as thirty years ago, this methodology of...
The solution of non-deterministic expert systems consists of two components –the solution reached an...
AbstractMost expert knowledge is ill-defined and heuristic. Therefore, many present-day rule-based e...
AbstractThis paper addresses the problem of modeling of expert knowledge as a starting point for inf...
AbstractA new technique of uncertainty management in expert systems is proposed. It is suggested tha...
Reasoning with uncertain information has received a great deal of attention recently, as this issue ...
Inference under uncertainty plays a crucial role in expert system and receives growing attention fro...
In this work we present a model for handling uncertain information. The concept of fuzzy knowledge-b...
The quality of an expert system, it is argued in this paper, is determined by the quality of its kno...
The quality of an expert system, it is argued in this paper, is determined by the quality of its kno...
AbstractMost expert knowledge is ill-defined and heuristic. Therefore, many present-day rule-based e...
AbstractThis paper compares four measures that have been advocated as models for uncertainty in expe...
The current paradigm of modelling uncertainty in expert systems knowledge bases using Certainty Fact...
A way to circumvent the awkwardness and constraints encountered while using Certainty Factors (CF) f...
This paper presents an approach to the explicit integration of uncertain reasoning mechanisms into ...
Although the first rule-based systems were created as early as thirty years ago, this methodology of...
The solution of non-deterministic expert systems consists of two components –the solution reached an...
AbstractMost expert knowledge is ill-defined and heuristic. Therefore, many present-day rule-based e...
AbstractThis paper addresses the problem of modeling of expert knowledge as a starting point for inf...
AbstractA new technique of uncertainty management in expert systems is proposed. It is suggested tha...
Reasoning with uncertain information has received a great deal of attention recently, as this issue ...
Inference under uncertainty plays a crucial role in expert system and receives growing attention fro...
In this work we present a model for handling uncertain information. The concept of fuzzy knowledge-b...
The quality of an expert system, it is argued in this paper, is determined by the quality of its kno...
The quality of an expert system, it is argued in this paper, is determined by the quality of its kno...
AbstractMost expert knowledge is ill-defined and heuristic. Therefore, many present-day rule-based e...
AbstractThis paper compares four measures that have been advocated as models for uncertainty in expe...