Agent based models of human systems, such as those found in behavioural economics, implement their agents intelligence through the use of simple rules. These models have proved to be worthwhile research tools. However, improving the outputs of these models will require a greater emphasis on the development of intelligence within the model agents. A deeper understanding of the cognitive process ...

This paper presents an original use of fuzzy logic for the design of Case-Based Reasoning (CBR) assistants, mainly for the case retrieval step. Our motivation comes from the importance of allowing for the expression of exible data (incomplete and imprecise data, preferences) in problem and case descriptions and to manage them in case retrieval. We present our retrieval system CAREFUL based on p...

Malaria, Typhoid, Tuberculosis, Sexually Transmitted Diseases, Urinary Tract Infection, Yellow fever, Hepatitis-B, Leprosy and Chicken Pox are the existing tropical diseases that are considered in this work. In sub-Saharan Africa, the application of fuzzy logic to the diagnosis of these diseases is still very sparse and in some places practically nonexistent. Fuzzy set theory and fuzzy logic ar...

In the component based software engineering approach, a software system is viewed as an assembly of reusable independently developed components. In order to produce automated tools to support the selection and assembly of components, rigorous specifications of components and performant retrieval and selection strategies based on these specifications are needed. In this article we propose a fuzz...

When designing any type of fuzzy rule based system, considerable effort is placed in identifying the correct number of fuzzy sets and the fine tuning of the corresponding membership functions. Once a rule base has been formulated a fuzzy inference strategy must be applied in order to combine grades of membership. Considerable time and effort is spent trying to determine the number of fuzzy sets...

The complexity of real-world problems entails many difficulties in the construction of artificial intelligence systems. In many cases, the acquisition, representation, and management of data in knowledge-based systems require methodological tools able to deal with uncertain, imprecise and incomplete knowledge. Knowledge-based systems based on fuzzy logic, for instance, have the capability of ma...

Nowadays, quick technological changes force companies to develop innovative products in an increasingly competitive environment. Therefore, how to enhance the time of new product development is very important. This design problem often lacks the exact formula for getting it, and highly depends upon human designers’ past experiences. For these reasons, in this work, a Casebased reasoning (CBR) s...

In this paper we present an application of rule-based expert systems to a farming problem. Concretely the prediction of the breeding value in Manchego ewes is studied for the early stage of their life in which the standard (BLUP) methodology cannot be applied. In this case the pedigree index (arithmetical mean between parents’ breeding value) is used to make the estimation. An alternative to th...

The paper presents a form of rendering classical mathematical notions by formal theories over suitable t-norm fuzzy logics in such a way that references to real numbers are eliminated from definitions and theorems, being removed to the standard semantics of fuzzy logic. Several examples demonstrate how this move conceptually simplifies the theory in exchange for non-classical reasoning, facilit...