In this work we analyze the problem of incorporating specificity to characterize defeat in a particular argumentative framework, called observation based defeasible logic programming (ODeLP) [1]. Eficiency is an important issues in ODeLP, since this framework has been de ned…

Parallel machine scheduling, involves the allocation of jobs to the system resources (a bank of machines in parallel). A basic model consisting of m machines and n jobs is the foundation of more complex models. Here, jobs are allocated according…

A solution of problems in multiagent systems involves representing beliefs of agents immersed in dynamic environments. Observation-based Defeasible Logic Programming (ODeLP) is an argument-based logic programming language that is used to represent an agent’s knowledge in the context of a…

Little has been written about the component provision problem (programming plans and domain concepts) for the repositories of knowledge in program understanding systems and reports that specifically address this issue are unknown. Model-driven and plan-driven approaches use repositories where construction…

In this paper, we build on previous work on Belief Revision operators based on the use of logic programming with Answer Set semantics as a representation language. We present a set of postulates for Answer Set Revision with respect to…

Defeasible Logic Programming (DeLP) is a knowledge representation and reasoning formalism that by combining Logic Programming with Defeasible Argumentation is able to represent incomplete and potentially contradictory information.
Within the field of Logic Programming, most of the implementations of Prolog…

In the last decade several ways to formalize defeasible reasoning have been studied. A particular approach, defeasible argumentation, has been particularly successful to achieve this goal.
The inference process of argument-based systems is based on the interaction of ar- guments…

Knowledge acquisition for systems based on knowledge can be called knowledge engineering, according to Feigenbaum (1980) who used the term to describe the reduction of a wide context of knowledge for a set of facts and rules. The term Knowledge…

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…

Frequently we become amazed with the increasing number of problems to be solved that fiourish while facing daily activities. Often, related to these problems we llave also an incredible amount oí data. Since we cannot allways afford time and resources…