Publications associées à Imitation (processus d'apprentissage)

Imitation Learning in Discounted Linear MDPs without exploration assumptions

Volkan Cevher, Efstratios Panteleimon Skoulakis, Luca Viano

We present a new algorithm for imitation learning in infinite horizon linear MDPs dubbed ILARL which greatly improves the bound on the number of trajectories that the learner needs to sample from the environment. In particular, we re- move exploration assu ...

2024

Follow the Clairvoyant: an Imitation Learning Approach to Optimal Control

Giancarlo Ferrari Trecate, Luca Furieri, John Lygeros, Andrea Martin, Florian Dörfler

We consider control of dynamical systems through the lens of competitive analysis. Most prior work in this area focuses on minimizing regret, that is, the loss relative to an ideal clairvoyant policy that has noncausal access to past, present, and future d ...

Elsevier2023

Many Are The Ways to Learn: Identifying multi-modal behavioral profiles of collaborative learning in constructivist activities

Pierre Dillenbourg, Barbara Bruno, Jauwairia Nasir, Aditi Kothiyal

Understanding how learners engage with learning technologies, and its relation with their learning, is crucial to the design of effective learning interventions. Assessing the learners’ state however, is non-trivial. Research suggests that performance is n ...

2021

Optimal Control Combining Emulation and Imitation to Acquire Physical Assistance Skills

Sylvain Calinon, Amirreza Razmjoo Fard, Teguh Santoso Lembono

paper studies exploiting action-level learning (imitation) in the optimal control problem context. Cost functions defined by the optimal control methods are similar to the goal-level learning (emulation) in animals. However, imitating the robot's or others ...

IEEE2021

Learning, Generating and Adapting Wave Gestures for Expressive Human-Robot Interaction

Sylvain Calinon

This study proposes a novel imitation learning approach for the stochastic generation of human-like rhythmic wave gestures and their modulation for effective non-verbal communication through a probabilistic formulation using joint angle data from human dem ...

ACM2020

Imitation, Proximity, and Growth - A Collective Swarm Dynamics Approach

Max-Olivier Hongler, Olivier Gallay, Fariba Hashemi

This paper is based on the premise that economic growth is driven by an interplay between innovation and imitation in an economy composed of interacting ̄rms operating in a stochastic environment. A novel approach to modeling imitation is presented based o ...

2019

An Approach for Imitation Learning on Riemannian Manifolds

Sylvain Calinon

In imitation learning, multivariate Gaussians are widely used to encode robot behaviors. Such approaches do not provide the ability to properly represent end-effector orientation, as the distance metric in the space of orientations is not Euclidean. In thi ...

2017

A Motion Capture Study to Measure the Feeling of Synchrony in Romantic Couples and in Professional Musicians

Pierre Magistretti, Delphine Preissmann, Joan Llobera Mahy

The feeling of synchrony is fundamental for most social activities and prosocial behaviors. However, little is known about the behavioral correlates of this feeling and its modulation by intergroup differences. We previously showed that the subjective feel ...

Frontiers Media2016

Tractable Approaches to Learning and Planning in High Dimensions

Leonidas Lefakis

The continuous increase, witnessed in the last decade, of both the amount of available data and the areas of application of machine learning, has lead to a demand for both learning and planning algorithms that are capable of handling large-scale problems. ...

EPFL2014

Learning control Lyapunov function to ensure stability of dynamical system-based robot reaching motions

Aude Billard, Seyed Mohammad Khansari Zadeh

We consider an imitation learning approach to model robot point-to-point (also known as discrete or reaching) movements with a set of autonomous Dynamical Systems (DS). Each DS model codes a behavior (such as reaching for a cup and swinging a golf club) at ...

Elsevier2014

Modeling the neural correlates of imitation from a neuropsychological perspective

Biljana Petreska von Ritter-Zahony

Imitation is a fundamental mechanism by which humans learn and understand the actions of others. This thesis addresses the low-level neural mechanisms underlying the imitation of meaningless gestures, using tools from computational neuroscience. We investi ...

EPFL2009

Using reinforcement learning for optimizing the reproduction of tasks in robot programming by demonstration

Florent Günter

As robots start pervading human environments, the need for new interfaces that would simplify human-robot interaction has become more pressing. Robot Programming by Demonstration (RbD) develops intuitive ways of programming robots, taking inspiration in st ...

EPFL2009

Neural modeling of the cortical processes underlying imitative behaviors : a dynamic neural field approach

Eric Sauser

Imitation is the ability to recognize, learn and reproduce the actions of others. In addition to facilitating the transmission of knowledge and skills, it has been suggested that this fundamental cognitive capacity is at the origin of other human faculties ...

EPFL2008

Continuous extraction of task constraints in a robot programming by demonstration framework

Sylvain Calinon

Robot Programming by Demonstration (RbD), also referred to as Learning by Imitation, explores user-friendly means of teaching a robot new skills. Recent advances in RbD have identified a number of key-issues for ensuring a generic approach to the transfer ...

EPFL2007

Using Reinforcement Learning to Adapt an Imitation Task

Aude Billard, Florent Günter

The goal of developing algorithms for programming robots by demonstration is to create an easy way of programming robots that can be accomplished by everyone. When a demonstrator teaches a task to a robot, he/she shows some ways of fulfilling the task, but ...

2007

Interferences in the Transformation of Reference Frames during a Posture Imitation Task

Aude Billard, Eric Sauser

We present a biologically-inspired neural model addressing the problem of transformations across frames of reference in a posture imitation task. Our modeling is based on the hypothesis that imitation is mediated by two concurrent transformations selective ...

2007

On Learning, Representing and Generalizing a Task in a Humanoid Robot

Aude Billard, Sylvain Calinon, Florent Günter

We present a Programming by Demonstration (PbD) framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to different contexts. We validate the architecture through a s ...

2007

Discriminative and Adaptive Imitation in Uni-Manual and Bi-Manual Tasks

Aude Billard, Sylvain Calinon, Florent Günter

This paper addresses the problems of what to imitate and how to imitate in simple uni- and bi-manual manipulatory tasks. To solve the what to imitate issue, we use a probabilistic method, based on Hidden Markov Models, for extracting the relative importanc ...

Elsevier2006

A Neurocomputational Model of an Imitation Deficit following Brain Lesion

Aude Billard, Biljana Petreska von Ritter-Zahony

This paper investigates the neural mechanisms of visuo-motor imitation in humans through convergent evidence from neuroscience. In particular, we consider a deficit in imitation following callosal brain lesion, based on the rational that looking at how imi ...

2006

Building Robota, a Mini-Humanoid Robot for the Rehabilitation of Children with Autism

Aude Billard

The Robota project constructs a series of multiple degrees of freedom doll-shaped humanoid robots, whose physical features resemble those of a human baby. The Robota robots have been applied as assistive technologies in behavioral studies with low-function ...

2007