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A chunking mechanism in a neural system for the parallel processing of propositional production rules.

Ernesto Burattini, A. Pasconcino, Guglielmo Tamburrini (1995)

Mathware and Soft Computing

The problem of extracting more compact rules from a rule-based knowledge base is approached by means of a chunking mechanism implemented via a neural system. Taking advantage of the parallel processing potentialities of neural systems, the computational problem normally arising when introducing chuncking processes is overcome. Also the memory saturation effect is coped with using some sort of forgetting mechanism which allows the system to eliminate previously stored, but less often used chunks....

A method for knowledge integration

Martin Janžura, Pavel Boček (1998)

Kybernetika

With the aid of Markov Chain Monte Carlo methods we can sample even from complex multi-dimensional distributions which cannot be exactly calculated. Thus, an application to the problem of knowledge integration (e. g. in expert systems) is straightforward.

A method for learning scenario determination and modification in intelligent tutoring systems

Adrianna Kozierkiewicz-Hetmańska, Ngoc Thanh Nguyen (2011)

International Journal of Applied Mathematics and Computer Science

Computers have been employed in education for years. They help to provide educational aids using multimedia forms such as films, pictures, interactive tasks in the learning process, automated testing, etc. In this paper, a concept of an intelligent e-learning system will be proposed. The main purpose of this system is to teach effectively by providing an optimal learning path in each step of the educational process. The determination of a suitable learning path depends on the student's preferences,...

A methodology for constructing fuzzy rule-based classification systems.

José María Fernández Garrido, Ignacio Requena Ramos (2000)

Mathware and Soft Computing

In this paper, a methodology to obtain a set of fuzzy rules for classification systems is presented. The system is represented in a layered fuzzy network, in which the links from input to hidden nodes represents the antecedents of the rules, and the consequents are represented by links from hidden to output nodes. Specific genetic algorithms are used in two phases to extract the rules. In the first phase an initial version of the rules is extracted, and in second one, the labels are refined. The...

A methodology for developing knowledge-based systems.

Juan Luis Castro, José Jesús Castro-Sánchez, Antonio Espin, José Manuel Zurita (1998)

Mathware and Soft Computing

This paper presents a methodology for developing fuzzy knowledge based systems (KBS), which permits a complete automatization. This methodology will be useful for approaching more complex problems that those in which machine learning from examples are successful.

A multicriteria genetic tuning for fuzzy logic controllers.

Rafael Alcalá, Jorge Casillas, Juan Luis Castro, Antonio González, Francisco Herrera (2001)

Mathware and Soft Computing

This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers in multicriteria complex problems. This tuning approach has some specific restrictions that make it very particular and complex because of the large time requirements existing due to the need of considering multiple criteria -which enlarges the solution search space-, and to the long computation time models usually used for fitness assessment. To solve these restrictions, two efficient genetic tuning...

A new approach to multiple fault diagnosis: A combination of diagnostic matrices, graphs, algebraic and rule-based models. The case of two-layer models

Antoni Ligęza, Jan Maciej Kościelny (2008)

International Journal of Applied Mathematics and Computer Science

The diagnosis of multiple faults is significantly more difficult than singular fault diagnosis. However, in realistic industrial systems the possibility of simultaneous occurrence of multiple faults must be taken into account. This paper investigates some of the limitations of the diagnostic model based on the simple binary diagnostic matrix in the case of multiple faults. Several possible interpretations of the diagnostic matrix with rule-based systems are provided and analyzed. A proposal of an...

Agent-oriented abstraction.

Jacques Calmet, Pierre Maret, Regine Endsuleit (2004)

RACSAM

We define an agent-oriented abstraction formalism devoted to generalized theories of abstraction that have been proposed in Artificial Intelligence. The model we propose extends the abstraction capabilities of the existing Agent-Oriented Programming paradigm. This short note reviews first the existing attempts to define abstraction in AI and in agent systems. Then, our model is introduced in terms of six definitions covering the concepts of agents, annotated knowledge, utility and society of agents....

Aggregation, Non-Contradiction and Excluded-Middle.

Ana Pradera, Enric Trillas (2006)

Mathware and Soft Computing

This paper investigates the satisfaction of the Non-Contradiction (NC) and Excluded-Middle (EM) laws within the domain of aggregation operators. It provides characterizations both for those aggregation operators that satisfy NC/EM with respect to (w.r.t.) some given strong negation, as well as for those satisfying them w.r.t. any strong negation. The results obtained are applied to some of the most important known classes of aggregation operators.

Analyzing the reasoning mechanisms in fuzzy rule based classification systems.

Oscar Cordón, María José del Jesús, Francisco Herrera (1998)

Mathware and Soft Computing

Fuzzy Rule-Based Systems have been succesfully applied to pattern classification problems. In this type of classification systems, the classical Fuzzy Reasoning Method classifies a new example with the consequent of the rule with the greatest degree of association. By using this reasoning method, we do not consider the information provided by the other rules that are also compatible (have also been fired) with this example.In this paper we analyze this problem and propose to use FRMs that combine...

Building a knowledge base for correspondence analysis.

M.ª Carmen Bravo Llatas (1994)

Qüestiió

This paper introduces a statistical strategy for Correspondence Analysis. A formal description of the choices, actions and decisions taken during data analysis is built. Rules and heuristics have been obtained from the application of this technique to real case studies.The strategy proposed checks suitability of certain types of data matrices for this analysis and also considers a guidance and interpretation of the application of this technique. Some algorithmic-like rules are presented and specific...

Communication with www in Czech

Lukáš Svoboda, Luboš Popelínský (2004)

Kybernetika

This paper describes UIO, a multi–domain question–answering system for the Czech language that looks for answers on the web. UIO exploits two fields, namely natural language interface to databases and question answering. In its current version, UIO can be used for asking questions about train and coach timetables, cinema and theatre performances, about currency exchange rates, name–days and on the Diderot Encyclopaedia. Much effort have been made into making addition of a new domain very easy. No...

Concept approximations based on rough sets and similarity measures

Jamil Saquer, Jitender Deogun (2001)

International Journal of Applied Mathematics and Computer Science

The formal concept analysis gives a mathematical definition of a formal concept. However, in many real-life applications, the problem under investigation cannot be described by formal concepts. Such concepts are called the non-definable concepts (Saquer and Deogun, 2000a). The process of finding formal concepts that best describe non-definable concepts is called the concept approximation. In this paper, we present two different approaches to the concept approximation. The first approach is based...

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