The Knowledge Engineering Suite is an ontology production method, based on relationship networks, for knowledge representation inside specific contexts. The production of these ontologies has three basic steps, since catching the client data, knowledge base creation, and information retrieval and…

James Reinders (Chief Evangelist of Intel® Software at Intel) and Jim Jeffers (Principal Engineer at Intel)
have gathered in this book the working knowledge of the people involved to prototype and productize the Intel® Xeon Phi coprocessor. This include…

The knowledge imperfections should be considered when modeling complex problems. A solution is to develop a model that reduces the complexity and another option is to represent the imperfections: uncertainty, vagueness and incompleteness in the knowledge base. This paper proposes…

It is interesting and important to compare, analyze and assess the alternative tools that could be used in the area of Knowledge Representation. In this paper we present a reasearch line associated to this goal: to formally establish the relation…

The development of systems with the ability to reason about change notion and actions has been of great importance for the artificial intelligence community. The definition and implementation of systems capable of managing defeasible, incomplete, unreliable, or uncertain information has…

The cognitive diagnosis is defined as the abstract process of gathering information about the student's learning and transforming that information based on instructional decisions. A model that captures the expert knowledge of experienced professors and is used to design a…

Our research project intends to build knowledge about HPC problems to be able to help local researchers. In order to advise users in choosing parallel machines to run their applications, we want to establish a general methodology, requiring as shallow…

This paper proposes an original generic hierarchical framework in order to facilitate the modeling stage of complex autonomous robotics mission planning problems with action uncertainties. Such stochastic planning problems can be modeled as Markov Decision Processes [5]. This work is…

Given an instance of an optimization problem together with an optimal solution, we consider the scenario in which this instance is modified locally. In graph problems, e. g., a singular edge might be removed or added, or an edge weight…

In a defeasible argumentation formalism, an argument is used as a defeasible reason for supporting conclusions. A conclusion q will be considered valid only when the argument that supports it become a justification. Building a justification involves the construction of…