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…

This work describes the ontology construction process for the development of an Intelligent System for the Organization and Retrieval of Knowledge in Biodiversity – SISBIO. The system aims at the production of strategic information for the biofuel chain Two main…

We discuss how data mining, patternbases and databases can be integrated into inductive databases, which make data mining an inductive query process. We propose a software architecture for such inductive databases, and extend this architecture to support the clustering of…

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…

Current reasoning systems attempt to model an agent's knowledge and interaction with its environment in a symbolic manner. This environment, its world is generally dynamic and changing due to natural evolution or the actions of other agents that are a…

One of the key aspects in the design of an architecture for autonomous agents is the way in which beleifs are revised in the face of new information. An intelligent agent must be prepared to handle new information (be it…

We present a socially inspired approach that allows agents in Multi-Agent Systems to speed up their own learning process through communication. Thereby, they are able to trade off impact of knowledge by mutation dependent on the recent performance of the…

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,…

Associating the pattern in text data with the pattern with time series data is a novel task. In this paper, an approach that utilizes the features of the time series data and domain knowledge is proposed and used to identify…

Artificial Intelligence has long dealt with the issue of finding a suitable formalization for reasoning with incomplete and potentially inconsistent information. Defeasible argumentation [SL92,CML00,PraVre99] has proven to be a successful approach in many respects, since it naturally resembles many aspects…