A new extension of fuzzy sets using rough sets: R-fuzzy sets

This paper presents a new extension of fuzzy sets: R-fuzzy sets. The membership of an element of a R-fuzzy set is represented as a rough set. This new extension facilitates the representation of an uncertain fuzzy membership with a rough approximation. Based on our definition of R-fuzzy sets and their operations, the relationships between R-fuzzy sets and other fuzzy sets are discussed and some examples are provided

On intuitionistic fuzzy negations and intuitionistic fuzzy extended modal operators. Part 2.

On intuitionistic fuzzy negations and intuitionistic fuzzy extended modal operators. Part 2

Robot competence development by constructive learning

This paper presents a constructive learning approach for developing sensor-motor mapping in autonomous systems. The system's adaptation to environment changes is discussed and three methods are proposed to deal with long term and short term changes. The proposed constructive learning allows autonomous systems to develop network topology and adjust network parameters. The approach is supported by findings from psychology and neuroscience especially during infants cognitive development at early stages. A growing radial basis function network is introduced as a computational substrate for sensory-motor mapping learning. Experiments are conducted on a robot eye/hand coordination testbed and results show the incremental development of sensory-motor mapping and its adaptation to changes such as in tool-use

Genetic evolution of sorting programs through a novel genotype-phenotype mapping

This paper presents an adaptable genetic evolutionary system, which includes an innovative approach to mapping genotypes to phenotypes through XML rules. The evolutionary system was originally created to evolve Regular Expressions (REs) to automate the extraction of web information. However, the system has been adapted to work with a completely different domain – Complete Software Programs – to demonstrate the flexibility of this approach. Specifically, the paper concentrates on the evolution of 'Sorting' programs . Experiments show that our evolutionary system is successful and can be adapted to work for challenging domains with minimum effort

An evolution of a complete program using XML-based grammar definition

XML technology is a technique to describe structured data that can be manipulated by different types of applications, especially to represent content on the Web. This paper presents a viable approach to automatically evolve a ‘sorting program’ by applying genetic programming and full syntax XML-based grammar definition to map the genotype to phenotype. The genotypes are composed of fixed-length blocks of genes that are made up of a series of integer values. The paper reports that our approach improves the structure of the grammar used in the mapping process, which guarantees that the generated program follows the correct syntax with no repair function, in comparison to earlier work. This allows more structured programs than earlier systems

An improved representation for evolving programs

A representation has been developed that addresses some of the issues with other Genetic Program representations while maintaining their advantages. This combines the easy reproduction of the linear representation with the inherita- ble characteristics of the tree representation by using fixed-length blocks of genes representing single program statements. This means that each block of genes will always map to the same statement in the parent and child unless it is mutated, irrespective of changes to the surrounding blocks. This method is compared to the variable length gene blocks used by other representations with a clear improvement in the similarity between parent and child. In addition, a set of list evaluation and manipulation functions was evolved as an application of the new Genetic Program components. These functions have the common feature that they all need to be 100% correct to be useful. Traditional Genetic Programming problems have mainly been optimization or approximation problems. The list results are good but do highlight the problem of scalability in that more complex functions lead to a dramatic increase in the required evolution time

Managing contradictory evidence

The paper draws on the theory of mass assignment to refine the underlying semantics of intuitionistic fuzzy sets. Inconsistency can arise from several sources and it is dealt with in different ways. All the representations of inconsistency and contradiction in this paper arise from considering restricting and positive evidence lattices. In particular this paper formally addresses the operators, intersection and conjunction in detail. Because union and disjunction are required to compute the values for intersection and conjunction these are also covered as part of the analysis

A stepwise evolution of functions

A Genotype-Phenotype mapping in most Genetic Programming (GP) systems uses a predefined and rigid grammar definition. This method has been successful in producing the required solution. However, it can only be used to solve a limited set of problems. In this paper, a Teachable GP (TGP) system is proposed. An external GP system evolves a complete computer program, which acceptable solution is then added automatically to the existing grammar definition as a function and made available to the TGP system. This dynamic grammar definition allows for a more complex program to be generated, solving more complex problems. Experiments are performed to compare performances between GP without the added function, GP with a user-defined function and GP with the evolved function and results shows that GP with an evolved function is comparable to the GP with user-defined function and outperformed GP without function

Semantic transfer and contradictory evidence in intuitionistic fuzzy sets

The relationship between object level intuitionistic fuzzy sets and predicate based intuitionistic fuzzy sets is explored. Mass assignment uses a process called semantic unification to evaluate the degree to which one set supports another, the inverse function is semantic separation. Intuitionistic fuzzy sets are mapped onto a mass assignment framework and the semantic unification operator is generalised to support both mass assignment and intuitionistic fuzzy sets, as is semantic separation. Transfer of inconsistent and contradictory evidence are also dealt with

Managing contradictory evidence

The paper draws on the theory of mass assignment to refine the underlying semantics of intuitionistic fuzzy sets. Inconsistency can arise from several sources and it is dealt with in different ways. All the representations of inconsistency and contradiction in this paper arise from considering restricting and positive evidence lattices. In particular this paper formally addresses the operators, intersection and conjunction in detail. Because union and disjunction are required to compute the values for intersection and conjunction these are also covered as part of the analysis