There exists a large amount of knowledge representation models. But most of them have significant limitations at the epistemic level. They do not have explanatory power. Most of them do not have means to represent some functional needs to work…

Fish disease diagnosis is a complicated process and requires high level of expertise, an expert system for fish disease diagnosis is considered as an effective tool to help fish farmers. However, many farmers have no computers and are not able…

The development of systems with the ability to reason about change notion and actions has been of great importance for the artificial intelligence community. The definition and implementation of systems capable of managing defeasible, incomplete, unreliable, or uncertain information has…

Classical methods for representing and reasoning with knowledge rely on the assumption that the available information is complete, certain and consistent. In real-world problems this is usually not the case, and Al has long dealt with the issue of finding…

In an m-machines n-jobs flow-shop sequencing problem each job consists of m operations and each operation requires a different machine, so n jobs have to be processed in the same sequence on m machines. The processing time of each job…

The cognitive diagnosis is defined as the abstract process of gathering information about the student's learning and transforming that information based on instructional decisions. A model that captures the expert knowledge of experienced professors and is used to design a…

The Requirements Engineering is fundamental part of the process of software development. Even if a program uses the most advanced technologies and has the best source code, it is not useful if it does not meet your requirements. The large…

This work extends the semantics and implementation of fuzzy prolog presented in [VGM02] in order to include Default Knowledge capability. The new semantic allows non-uniform default assumptions and has Closed World Assumption (CWA) and Open World Assumption (OWA) as particular…

The Knowledge Engineering Suite is an ontology production method, based on relationship networks, for knowledge representation inside specific contexts. The production of these ontologies has three basic steps, since catching the client data, knowledge base creation, and information retrieval and…

It is interesting and important to compare, analyze and assess the alternative tools that could be used in the area of Knowledge Representation. In this paper we present a reasearch line associated to this goal: to formally establish the relation…