A cognitive robot is an autonomous robot that is capable of inference, perception, and learning mimicking the cognitive mechanisms of the brain. The underpinning technologies for cognitive robots are the cognitive knowledge base (CKB) and the cognitive learning engine (CLE). This paper explores the cognitive foundations and denotational mathematical means of CLE and CKB for cognitive robotics. ...

This paper discusses learning in hybrid models that goes beyond simple classification rule extraction from backpropagation networks. Although simple rule extraction has received a lot of research attention, we need to further develop hybrid learning models that learn autonomously and acquire both symbolic and subsymbolic knowledge. It is also necessary to study autonomous learning of both subsy...

In this paper we argue that the potential of e-learning systems for active and autonomous knowledge acquisition and use can be substantially enhanced by exploiting the personalization capabilities of concept-oriented content management. Content and implementation personalization are essential services provided by research-oriented content management systems. Personalized concept understanding a...

Numerous groups have applied a variety of deep learning techniques to computer vision problems in highway perception scenarios. In this paper, we presented a number of empirical evaluations of recent deep learning advances. Computer vision, combined with deep learning, has the potential to bring about a relatively inexpensive, robust solution to autonomous driving. To prepare deep learning for ...

This paper presents a hand-eye-head system which learns to perform temporal actions. In this system, the robot learns how to control its hand according to what is seen and the speciic mission. The learning process is interactive and on-line. Several networks which store the learned information are automatically generated through learning processes. The hierarchical structure of the network allo...

This paper describes a theory called Goal-Directed Learning (gdl) that uses the principle of decision theory to choose learning tasks. The expected utility of being able to predict various features of the environment is computed and those with highest expected utility can be used as learning goals, which an agent's inductive mechanism should form theories to predict. We present a general decisi...

The Internet provides learners with unprecedented opportunities; student can not only share the learning resources, but also overcome the obstacles of time and space. The new teaching model make full use of the advantages of modern information technology, especially the network multimedia technology, so that English teaching has been developed toward the direction as autonomous learning and col...

AI seems to be developing toward a theory of intelligent agents (IA), however, the theoretical basis which should underly the notion of agency has remained strikingly underdeveloped. This paper is intended to improve on this situation, by analysing the most basic notions necessary for a theory of agency: action, self, control, autonomy and adaptivity. Our main thesis is that autonomy is the ess...

AI seems to be developing toward a theory of intelligent agents (IA), however, the theoretical basis which should underly the notion of agency has remained strikingly underdeveloped. This paper is intended to improve on this situation, by analysing the most basic notions necessary for a theory of agency: action, self, control, autonomy and adaptivity. Our main thesis is that autonomy is the ess...