SUBJECT-IVE AND OBJECTIVE

The Makeready Arch Ive

Discrimination- Ive Io

This paper presents a new approach to constructive induction, Discrimination-Based Constructive induction(DBC), which invents useful predicates in learning relations. Triggered by failure of selective induction, DBC finds a minimal set of variables forming a new predicate that discriminates between positive and negative examples, and induces a definition of the invented predicate. If necessary,...

Esist Ive Techno

In this paper, we introduce a new touch sensor design, which we refer to as hybrid tactile sensor. It combines the simplicity of analog touch sensing, which is widely used in electronic touch screens and touchpads, with the ability of shape discrimination of the array touch senstactile sensors designed for robotics applidescribe the construction techniques of the sensor, its modelling, and shap...

Nduct Ive Ilist Ic Ai

This paper describes an inductive learning method in probabilistic domain. It acquires an appropriate probabilistic model from a small amount of observation data. In order to derive an appropriate probabilistic model, a presumption tree with least description length is constructed. Description length of a presumption tree is defined as the sum of its code length and log-likelihood. Using a cons...

OPTIMIZATION OF LINEAR OBJECTIVE FUNCTION SUBJECT TO FUZZY RELATION INEQUALITIES CONSTRAINTS WITH MAX-AVERAGE COMPOSITION

In this paper, the finitely many constraints of a fuzzy relationinequalities problem are studied and the linear objective function on the regiondefined by a fuzzy max-average operator is optimized. A new simplificationtechnique which accelerates the resolution of the problem by removing thecomponents having no effect on the solution process is given together with analgorithm and a numerical exa...