In the context of culture-aware robotics, we propose a method for the explicit, on-line mapping between cultural variables and robot behaviour parameters which relies on the linguistic variable formalism, fuzzy clustering and the principles of fuzzy controllers. As a case study, we consider the adaptation of the Human-Robot conversational distance to Hofstede’s cultural dimension of Individualism.

Various inductive machine learning approaches and problem specificstious are analysed from s logical perspective. This results in a unifying framework for the logical aspects of inductive machine learning and data mining. The framework exp]~R logical ,~m;l,~Tities s~d differences between different machine learning settings, and allows us to relate past and present work on inductive machine lear...

Multidimensional association rule mining searches for interesting relationship among the values from different dimensions/attributes in a relational database. In this method the correlation is among set of dimensions i.e., the items forming a rule come from different dimensions. Therefore each dimension should be partitioned at the fuzzy set level. This paper proposes a new algorithm for genera...

This paper proposes a new type of a support vector machine which uses a kernel constituted from fuzzy basis functions. The proposed network combines the characteristics both of a support vector machine and a fuzzy system: high generalization performance, even when the dimension of the input space is very high, structured and numerical representation of knowledge and ability to extract linguisti...

We present a survey of some results published recently by the authors regarding fuzzy aspects finitely supported structures. Considering notion finite support, we introduce new degree membership association between crisp set and function modelling for each element in set. define study notions invariant set, complete lattices, monoids strong inductive sets. The (fuzzy) subgroups an group, as wel...

We construct a hereditary shape equivalence that raises transfinite inductive dimension from ω to ω + 1. This shows that ind and Ind do not admit a geometric characterisation in the spirit of Alexandroff’s Essential Mapping Theorem, answering a question asked by R. Pol.

This paper extends the result of [2] in order to use the inductive approach to prove Gaussian asymptotic behaviour for models with critical dimension other than 4. The results are applied in [3] to study sufficiently spread-out lattice trees in dimensions d > 8 and may also be applicable to percolation in dimensions d > 6.

The evolutionary learning of fuzzy neural networks (FNN) consists of structure learning to determine the proper number of fuzzy rules and parameters learning to adjust the network parameters. Many optimization algorithms can be applied to evolve FNN. However the search space of most algorithms has fixed dimension, which cannot suit to dynamic structure learning of FNN. We propose a novel techni...