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…

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…

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…

The goal of this work involves the developing of an argumentation-based formalism that an agent could use for constructing plans. In this formalism, agents will have certain knowledge about the world, and a set of actions that they will be…

This paper presents a proposal for an architecture that integrates knowledge discovery systems (automatic acquisition) and knowledge based systems (experts systems). This work formulates considerations over the viability of the implementation of this architecture according to the advance of the…

The design of intelligent agents is a key issue for many applications. Although there is no universally accepted de nition of intelligence, a notion of rational agency has been proposed as an alternative for the characterization of intelligent agency.
Modeling…

The tools for fault impact analysis are important for the deployment of critical mission systems. These tools can be also used as a development phase aid. We introduce several concepts related to "business alarms". Business alarms are an approximation to…

Argumentation systems have substantially evolved in the past few years, resulting in adequate tools to model
some forms of common sense reasoning. This has sprung a new set of argument-based applications in diverse
areas.
In previous work, we defined how…

The Knowledge Engineering Suite is an ontology production method, based on relationship networks, for knowledge representation inside specific contexts. The production of these ontologies has three basic steps, since catching the client data, knowledge base creation, and information retrieval and…

This study investigates an approach of knowledge discovery and data mining in insufficient databases. An application of Computational Taxonomy analysis demonstrates that the approach is effective in such a data mining process. The approach is characterized by the use ot…