An automatic knowledge acquisition method for switching sequences and it´s evaluation

This paper presents the development and maintenance of intelligent `switching sequence generation´ systems. The authors have developed a new framework which can construct and update its knowledge base without external influence. This paper proposes an automatic knowledge acquisition method, a key part of the intelligent system architecture which is realized by means of the machine learning paradigm. This paper introduces a new knowledge acquisition method and discusses the evaluation and the extension for the purpose of its practical use