Task-parameterized models of movements aim at automatically adapting movements to new
situations encountered by a robot. The task parameters can, for example, take the form of …

Intelligent adaptive curiosity (IAC) was initially introduced as a developmental mechanism
allowing a robot to self-organize developmental trajectories of increasing complexity without …

In this paper we build an imitation learning algorithm for a humanoid robot on top of a
general world model provided by learned object affordances. We consider that the robot has …

This chapter reviews several approaches to the problem of learning by imitation in robotics.
We start by describing several cognitive processes identified in the literature as necessary …

Gestures are characterized by intermediary or final landmarks (real or virtual) in task space
or joint space that can change during the course of the motion, and that are described by …

The paper describes and formalizes the concepts and assumptions involved in Learning
from Demonstration (LFD), a common learning technique used in robotics. LFD-related …

Motion mapping is an important part in human–robot cooperation. In this paper, a novel
concept of virtual-joint based similarity criteria is proposed for flexible and efficient …

Due to the limitations on the capabilities of current robots regarding task learning and
performance, imitation is an efficient social learning approach that endows a robot with the …

Social learning in robotics has largely focused on imitation learning. Here we take a broader
view and are interested in the multifaceted ways that a social partner can influence the …

In this article we propose a computational model that describes how observed behavior can
influence an observer's own behavior, including the acquisition of new task descriptions …