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…

Knowledge-intensive processes are widely used to recover from errors, handle exceptional cases and complaints, and to improve or adapt a process itself. In this context, evolved Business-Process Reengineering (BPR) techniques are changing to give some answers to this reality. In…

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 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…

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…

In the last years there has been an increasing demand of a variety of logical systems, prompted
mostly by applications of logic in AI, logic programming and other related areas. Labeled Deductive
Systems (LDS) were developed as a °exible methodology…

Artificial Intelligence (AI) has long dealt with the issue of finding a suitable formalization for commonsense reasoning. Defeasible argumentation has proven to be a successful approach in many respects, proving to be a confluence point for many alternative logical frameworks.…

When certain enterprise domain needs to make an unusual decision, it will probably require new kind of information. If the interaction model among domains cannot be defined because the decision scenarios are unpredictable, the system itself must search the required…

It is commonly acknowledged that we need to accept and handle uncertainty when reasoning with real world data. The most profoundly studied measure of uncertainty is the probability. However, the general feeling is that probability cannot express all types of…

In this article we present a generalized dynamic argumentation framework that handles arguments expressed in an abstract language assumed to be some first order logic fragment. Once the formalism is presented, we propose a reification to the description logic ALC…