This paper describes a method of supervised learning based on forward selection branching. This method improves fault tolerance by means of combining information related to general...
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Abstract. This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced ...
This paper presents a novel framework called proto-reinforcement learning (PRL), based on a mathematical model of a proto-value function: these are task-independent basis function...
The paradox of fuzzy modeling is recognized due to the co-existence of its effectiveness of solving uncertain problems in the real world and the skepticism of its reasonability in ...