— We are interested in transferring control policies for arbitrary tasks from a human to a robot. Using interactive demonstration via teloperation as our transfer scenario, we ca...
In this paper we investigate the role of reflection in simulation based learning by manipulating two independent factors that each separately lead to significant learning effects, ...
Several recent techniques for solving Markov decision processes use dynamic Bayesian networks to compactly represent tasks. The dynamic Bayesian network representation may not be g...
Generally speaking, in the e-learning systems, a course is modeled as a graph, where each node represents a knowledge node (KU) and two nodes are connected to form a semantic netw...
We present an approach for the supervised online learning of object representations based on a biologically motivated architecture of visual processing. We use the output of a rece...