We present an application of the analytical inductive programming system Igor to learning sets of recursive rules from positive experience. We propose that this approach can be used within cognitive architectures to model regularity detection and generalization learning. Induced recursive rule sets represent the knowledge which can produce systematic and productive behavior in complex situation...

In this paper, supervised learning for Self-Generating Neural Networks (SGNN) method, which was originally developed for the purpose of unsupervised learning, is discussed. An information analytical method is proposed to assign weights to attributes in the training examples if class information is available. This significantly improves the learning speed and the accuracy of the SGNN classiier. ...

Education is one of the efforts to improve intelligence next generation a nation. considered an important and strategic factor in national development, with oriented towards improving quality human resources. In dealing problems social life, course, every student needs develop process skills. The skills each will be honed by itself if students have better. It relates physical mental that result...

While operational space control is of essential importance for robotics and well-understood from an analytical point of view, it can be prohibitively hard to achieve accurate control in face of modeling errors, which are inevitable in complex robots, e.g., humanoid robots. In such cases, learning control methods can offer an interesting alternative to analytical control algorithms. However, the...

As higher education diversifies its delivery modes, our ability to use the predictive and analytical power of educational data mining (EDM) to understand students’ learning experiences is a critical step forward. The adoption of EDM by higher education as an analytical and decision making tool is offering new opportunities to exploit the untapped data generated by various student information sy...