Transfer learning addresses the problem of how to leverage knowledge acquired in a
source domain to improve the accuracy and speed of learning in a related target domain …

One of the major stumbling blocks for artificial intelligence remains the commonsense
knowledge problem. It is not clear how we could go about building a program which has all …

Although robots have been widely used in a variety of fields, the idea of enabling them to
perform multiple tasks in the same way that humans do remains a difficulty. To solve this, we …

This position paper argues the case for the application of constructivist theories to Artificial
Intelligence, with particular emphasis on Piaget's theory. The idea of building an artificial …

We present a framework for the programming of manipulation behavior by means of an
intrinsic reward function that encourages the building of deep control knowledge. We show …

We address the generalization and transfer of sensorimotor programs in robot systems. We
use a factorable control-based approach that provides a natural, discrete abstraction of the …

This dissertation investigates two complementary ideas in the literature on machine learning
and robotics—those of embodiment and intrinsic motivation—to address a unified framework …

Özet Klasik makine öğrenmesi teknikleri, sadece yeterli miktarda ve uygun eğitim verisi
olduğunda verimli çalışabilmektedir. Gerçek hayatta ise makine öğrenmesi yöntemlerini tam …

With the promotion of artificial intelligence technology, service robots play an increasingly
important role in human life. Compared with industrial robots, the audience of service robots …

AI constructivism as inspired by Jean Piaget, described and surveyed by Frank Guerin, and
representatively implemented by Gary Drescher seeks to create algorithms and knowledge …