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…

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…