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…

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…

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…

In logic programs, negation-as-failure has been used both for representing negative information and for providing default nonmonotonic inference. In this paper we argue that this twofold role is not only unnecessary for the expressiveness of the language, but it also…

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…

Mountain papaya fruits (Vasconcella pubescens) were tested for firmness with a nondestructive acoustic method for 14 days after harvest. The response of each fruit was analyzed with the Fourier transform to obtain a firmness index (FI) based on the second…

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…

A multiagent system (MAS) is made up of multiple interacting autonomous agents. It can be viewed as a society in which each agent performs its activity, cooperating to achieve common goals, or competing for them. Thus, every agent has the…

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…

Nowadays, data intensive applications are in constant demand and there is need of computing environments with better intelligent capabilities than those present in today's Database Management Systems (DBMS). To build such systems we need formalisms that can perform complicate inferences,…