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.

In omplete information is a problem in many aspe ts of a tual environments. Further- more, in many s enarios the knowledge is not represented in a risp way. It is ommon to nd fuzzy on epts or problems with…

In this work two declarative approaches based on the BDI theory are studied, an agent programming language 3APL and an agent architecture that uses defeasible argumentation for knowledge representation and reasoning. Based on that study and considering that in 3APL…

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…

Four different leaf extracts of B. microstachya var. massambabensis were studied to evaluate their antioxidant capacity by using three in vitro methods, with Ginkgo biloba and Trolox® as the standards. With the DPPH and ABTS·+ methods, the antioxidant activity of…

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…