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…

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.

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,…

Effective document retrieval using domain knowledge and semantics is one of the major challenges in Information Retrieval. Over the last years, there has been a growing interest in ontologies as an artifact for human knowledge representation and a critical component…

In the restricted single-machine common due date problem the goal is to find a schedule for the n jobs which jointly minimizes the sum of earliness and tardiness penalties, while for the weighted tardiness problem the goal is to find…

Evolutionary algorithms (EAs) are merely blind search algorithms, which only make use of the relative fitness of solutions, but completely ignore the nature of the problem. Their performance can be improved by using new multirecombinative approaches, which provide a good…

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…

A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. As it is well known, the use of prior knowledge can dramatically improve the performance and quality…

A fuzzy controller is usually designed by formulating the knowledge of a human expert into a set of linguistic variables and fuzzy rules. As it is well known, the use of prior knowledge can dramatically improve the performance and quality…

Knowledge representation models are very important in the design of intelligent agents because they provide with mechanisms to manage beliefs and their dynamics. In this paper, we propose the use of AnsProlog* as a knowledge representation language, and develop a…