Catálogo de publicaciones - libros

The paper follows the path that AI has taken since its beginnings until the brink of the third millennium. New areas, such as Agents, have sprout; other subjects (Learning) have diminished. Areas have separated (Vision, Image Processing) and became independent, self-standing. Some areas have acquired formality and rigor (Vision). Important problems (Spelling, Chess) have been solved. Other problems (Disambiguation) are almost solved or about to be solved. Many challenges (Natural language translation) still remain. A few parts of the near future are sketched through predictions: important problems about to be solved, and the relation of specific AI areas with other areas of Computer Science.

We explore the properties of subgraphs (called Markovian subgraphs) of a decomposable graph under some conditions. For a decomposable graph and a collection of its Markovian subgraphs, we show that the set of the intersections of all the neighboring cliques of contains . We also show that holds for a certain type of which we call a maximal Markovian supergraph of . This graph-theoretic result is instrumental for combining knowledge structures that are given in undirected graphs.

A simple representation framework for ontological knowledge with dynamic and deontic characteristics is presented. It represents structural relationships (-, /), dynamic relationships (actions such as , , etc.), and conditional relationships (--). As a case study, we apply our representation language to the task of requirements elicitation in software engineering. We show how our pre-conceptual schemas can be obtained from controlled natural language discourse and how these diagrams can be then converted into standard UML diagrams. Thus our representation framework is shown to be a useful intermediate step for obtaining UML diagrams from natural language discourse.

This paper presents a formal model of the knowledge representation scheme KRFP based on the Fuzzy Petri Net (FPN) theory. The model is represented as an 11-tuple consisting of the components of the FPN and two functions that give semantic interpretations to the scheme. For the scheme a fuzzy recognition-inference procedure, based on the dynamical properties of the FPN and the inverse –KRFP scheme, is described in detail. An illustrative example of the fuzzy recognition algorithm for the knowledge base, designed by the KRFP, is given.

This paper addresses an extended order-sorted logic that can deal with structured sort symbols consisting of multiple ordinary words like noun phrases, and proposes inference rules for the resolution process semantically interpreting the sort symbols word by word. Each word in a sort symbol can represent a general concept or a particular object, which is a variable or a constant having the word itself as the sort symbol. It may be a proper noun or variable. This paper also describes an application scheme of the proposed inference rules and an algorithm for judging the subsort relation between complex sort symbols.

In this paper we introduce preference rules which allow us to specify preferences as an ordering among the possible solutions of a problem. Our approach allow us to express preferences for general theories. The formalism used to develop our work is Answer Set Programming. Two distinct semantics for preference logic programs are proposed. Finally, some properties that help us to understand these semantics are also presented.

This paper presents an object-oriented framework based on the E-R computational creativity model. It proposes a generic architecture for solving problems that require a certain amount of creativity. The design is based on advanced Software Engineering concepts for object-oriented Framework Design. With the use of the proposed framework, the knowledge of the E-R computational model can be easily extended. This model is important since it tries to diagram the human creativity process when a human activity is done. The framework is described together with two applications under development which implement the framework.

This article presents the implementation of first-order interval type-1 non-singleton type-2 TSK fuzzy logic system (FLS). Using input-output data pairs during the forward pass of the training process, the interval type-1 non-singleton type-2 TSK FLS output is calculated and the consequent parameters are estimated by back-propagation (BP) method. In the backward pass, the error propagates backward, and the antecedent parameters are estimated also by back-propagation. The proposed interval type-1 non-singleton type-2 TSK FLS system was used to construct a fuzzy model capable of approximating the behaviour of the steel strip temperature as it is being rolled in an industrial Hot Strip Mill (HSM) and used to predict the transfer bar surface temperature at finishing Scale Breaker (SB) entry zone, being able to compensate for uncertain measurements that first-order interval singleton type-2 TSK FLS can not do.

This paper addresses state estimation of discrete event systems () using a fuzzy reasoning approach; a method for approximating the current state of with uncertainty in the duration of activities is presented. The proposed method is based on a specification given as a fuzzy timed Petri net in which fuzzy sets are associated to places; a technique for the recursive computing of imprecise markings is given, then the conversion to discrete marking is presented.

In this paper we investigate real-time adaptive extensions of our fuzzy logic based approach for providing biologically based motivations to be used in evolutionary mobile robot learning. The main idea is to introduce active battery level sensors and recharge zones to improve robot behavior for reaching survivability in environment exploration. In order to achieve this goal, we propose an improvement of our previously defined model, as well as a hybrid controller for a mobile robot, combining behavior-based and mission-oriented control mechanism. This method is implemented and tested in action sequence based environment exploration tasks in a Khepera mobile robot simulator. We investigate our technique with several sets of configuration parameters and scenarios. The experiments show a significant improvement in robot responsiveness regarding survivability and environment exploration.