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…

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…

The notion of context and its importance in knowledge representation and nonmonotonic reasoning was first discussed in Artificial Intelligence by John McCarthy.
Ever since, contexts have found many applications in developing knowledge-based reasoning systems.
Defeasible argumentation has gained wide acceptance…

The problem of speeding up ínference has proved to be important in argumentative systems. When computing dialectical structures, several paths are searched (called argumentation lines), many of which will eventually prove useless. Morover, the performance of backward chainers degrades quickly…

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…

The appearance and continuous growth of virtual communities on the web imposes the challenge of coping with the large amount of information and knowledge these communities produce. The Semantic Web with its set of standards and technologies provides the basic…

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…

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…

The purpose of this paper is to describe how some theorems about constructions in categories can be seen as a way of doing generic programming. No prior knowledge of category theory is required to understand the paper.
We explore the…

We have developed a distributed DSS able to work in a dynamic way. This system is based on the use of mobile agents, which receive the user's queries and visit the DSS domains gathering the required information. One of the…