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 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…

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…

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.…

This work extends the semantics and implementation of fuzzy prolog presented in [VGM02] in order to include Default Knowledge capability. The new semantic allows non-uniform default assumptions and has Closed World Assumption (CWA) and Open World Assumption (OWA) as particular…

One of the key aspects in the design of an architecture for autonomous agents is the way in which beleifs are revised in the face of new information. An intelligent agent must be prepared to handle new information (be it…

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…

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…