The general objective of this thesis is the development of an adaptive technique for extracting knowledge in large databases. Nowadays, technology allows storing huge volumes of information. For this reason, the availability of techniques that allow, as a first stage,…

Most unsupervised indigenous knowledge (IK) are known to be very useful in combating critical health issues as well as being dangerous if the administration is abused. Despite the fact that these locally prepared herbal medicine are not encouraged to be…

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 knowledge imperfections should be considered when modeling complex problems. A solution is to develop a model that reduces the complexity and another option is to represent the imperfections: uncertainty, vagueness and incompleteness in the knowledge base. This paper proposes…

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…

The development of isolated agents involves the manipulation of components such as actions, mental attitudes and decisions. Multi-agent systems have to deal with these components from different agents, without to forget the privacy and autonomy of each agent. For programming…

In this work we present an approach to model an action-oriented system controlled by BDI agents using a defeasible argumentation formalism to represent its knowledge. Here, our main concern will be modelling the software agents that drive the physical robots.

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…