We present a socially inspired approach that allows agents in Multi-Agent Systems to speed up their own learning process through communication. Thereby, they are able to trade off impact of knowledge by mutation dependent on the recent performance of the…

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…

Most of the current wireless sensor networks are built for specific applications, with a tight coupling between them and the underlying communication protocols. We present a more flexible architectural approach for building WSNs, in which application-specific features are decoupled from…

Current interactive multimedia learning software can not be accessed by learners with disabilities. This is the case for students with vision disabilities. Modeling techniques are necessary to map real world experiences to virtual worlds by using 3D auditory representations of…

Information systems play an ever-increasing key role in our society. In particular, data intensive applications are in constant demand and there is need of computing environments with much more intelligent capabilities than those present in today’s Data-base Management Systems (DBMS).…

This article presents a procedure for constructing a taxonomy of COTS products in the field of Requirements Engineering (RE). The taxonomy and the obtained information reach transcendental benefits to the selection of systems and tools that aid to RE-related actors…

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…

This paper presents a neuro-fuzzy network where all its parameters can be tuned simultaneously using Genetic Algorithms. The approach combines the merits of fuzzy logic theory, neural networks and genetic algorithms. The proposed neuro-fuzzy network does not require a priori…

Complex control tasks may be solved by dividing them into a more specific and more easily handled subtasks hierarchy. Several authors have demonstrated that the incremental layered evolution paradigm allows obtaining controllers capable of solving this type of tasks. In…

This work is focussed on the development and analysis of a new class of algorithms, called cellular memetic algorithms (cMAs), which will be evaluated here on the satisfiability problem (SAT). For describing a cMA, we study the effects of adding…