A model of self-modificated predicate network with cells implementing predicate formulas in the form of elementary conjunction is suggested. Unlike a classical neuron network the proposed model has two blocks: a training block and a recognition block. If a recognition block has a mistake then the control is transferred to a training block. Always after a training block run the configuration of a recognition block is changed. The base of the proposed predicate network is logic-objective approach to AI problems solving and level description of classes.
|Название основной публикации||International Journal on Information Theory and Applications|
|Страницы||245 – 257|
|Состояние||Опубликовано - 2015|
|Опубликовано для внешнего пользования||Да|