Goal-based Open-ended Autonomous Learning Robots

Risultati finali

Communication activities, supported by services from Robohub within the collaboration with them, and Blogs, in particular within the Digital Europe Agenda system.

Professional video on GOAL3 Demo

Professional video on GOAL3 Demo.

Project web-site and logo

First version of project web-site. Logo of project. The maintenance of the web-site is an activity that will last during the whole project. The consortium, under the lead of CNR, will work to design the web-site structure and logo, and to populate it with contents related to the project. CNR will pay some professionals for support on technical aspects contributing to the realisation of the web-site.

Professional video on GOAL4 Demo.
Professional video on GOAL2 Demo

Professional video on the second demo GOAL2 .

Action Check Meeting 2

Draft agenda and list of presentations of Check Meeting 2.

Action Check Meeting 3

Draft agenda and list of presentations of Check Meeting 3.

Action Check Meeting 1

Draft agenda and list of presentations of Check Meeting 1.

Dissemination and Exploitation Plan: first version

Plan of dissemination and exploitation: first compilation. CNR will lead the whole plan compilation. As stated in the submitted proposal, TUDa will lead the exploitation section of the plan.

Goal-based skill learning: first results

Algorithms allowing autonomous robots to learn large repertoires of flexible skills based on goals.

Scientific publications and conferences

Publications in journals, and presentations at conferences and other similar scientific events, on the project results.

Self goal-generation: consolidated results

Goal-formation/architectures to acquire sequential/hierarchical skills.

GOAL in infants and its models: first results

Report on how contingencies and goals are discovered and drive autonomous motor learning in infants, and formalisation of discovered mechanisms in computational models.

GOAL in infants and its models: consolidated results

Report on principles of generalisation, transfer, and agency, related to contingencies and goals, in infants and robots.

Dissemination and Exploitation Plan: third version

Plan of dissemination and exploitation: revision leading to the third version of the plan. CNR will lead the whole plan compilation. As stated in the submitted proposal, TUDa will lead the exploitation section of the plan.

Journal Special Issue

Journal Special Issue on the project results, hosted in a relevant journal.

Self goal-generation: first results

Mechanisms for goal formation, and architectures/mechanisms to support open-ended learning of skills in robots.

Goal-based skill learning: consolidated results

Algorithms to learn repertoires of flexible sequential/hierarchical skills.

Dissemination and Exploitation Plan: second version

Plan of dissemination and exploitation: revision leading to the second version of the plan. CNR will lead the whole plan compilation. As stated in the submitted proposal, TUDa will lead the exploitation section of the plan.

International Workshop

International Workshop on the project topics, involving researchers from both the project consortium and the scientific community beyond it.

Industry fair: second participation

Second participation to an industry fair and contacts with companies for the possible exploitation of the project outcomes.

Second open-ended learning competition

Second open-ended learning competition and improvement of open-ended learning benchmark.

Second ethical implications workshop

Organisation of the second workshop on the possible implications of open-ended learning for society.

First ethical implications workshop

Organisation of the first workshop on the possible implications of open-ended learning for society.

Industry fair: third participation

Third participation to an industry fair and contacts with companies for the possible exploitation of the project outcomes.

First open-ended learning competition

First open-ended learning competitions related to open-ended learning, supporting the definition of a benchmark for open-ended learning.

International Summer School

International Summer School on the project topics and approach to open-ended learning.

Industry fair: first participation

First participation to an industry fair and contacts with companies for the possible exploitation of the project outcomes.

GOAL1 Demonstrator

GOAL1 demonstrator will show: (a) the set-ups used in the Demos; (b) the operation of the basic robot architectures supporting open-ended learning of GOAL2/GOAL3; (c) the successful accomplishment of initial open-ended learning processes.

GOAL4 Demonstrator

GOAL4 demonstrator will show a solution to the tidy-up challenge in a real-life scenario. The pivotal element of the demo is that the robot will solve the challenge by relying on knowledge and skills autonomously acquired through a prolonged GOAL-based development preceding the challenge itself, without knowing in advance the type of initial object configuration, object misplacement, and specific objects involved. The autonomous-learning abilities of the robots will be shown by giving the robots new objects.

GOAL2 Demonstrator

GOAL2 demonstrator will show robots that can learn several different skills in an open-ended fashion.

GOAL3 Demonstrator

GOAL3 demonstrator will show robots that not only can learn several different skills with little supervision, but can also learn to perform each skill in several different conditions.

Plan for Open Data Pilot: first version

First document describing the data management plan to comply to the Open Data Pilot initiative.

Plan for Open Data Pilot: second version

Revised second document describing the data management plan to comply to the Open Data Pilot initiative.

Plan for Open Data Pilot: third version

Third revised document describing the data management plan to comply to the Open Data Pilot initiative.

Pubblicazioni

Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks

Autori: Tanneberg, Daniel; Peters, Jan; Rueckert, Elmar
Pubblicato in: Neural Networks, Numero 1, 2018, ISSN 0893-6080
Editore: Pergamon Press Ltd.

Detection of sensorimotor contingencies in infants before the age of 1 year: A comprehensive review.

Autori: Lisa Jacquey, Jacqueline Fagard, Rana Esseily, J. Kevin O'Regan
Pubblicato in: Developmental Psychology, Numero 56/7, 2020, Pagina/e 1233-1251, ISSN 0012-1649
Editore: American Psychological Association
DOI: 10.1037/dev0000916

General differential Hebbian learning: Capturing temporal relations between events in neural networks and the brain

Autori: Stefano Zappacosta, Francesco Mannella, Marco Mirolli, Gianluca Baldassarre
Pubblicato in: PLOS Computational Biology, Numero 14/8, 2018, Pagina/e e1006227, ISSN 1553-7358
Editore: Public Library Of Science
DOI: 10.1371/journal.pcbi.1006227

Sensorimotor Contingencies as a Key Drive of Development: From Babies to Robots

Autori: Lisa Jacquey, Gianluca Baldassarre, Vieri Giuliano Santucci, J. Kevin O’Regan
Pubblicato in: Frontiers in Neurorobotics, Numero 13, 2019, ISSN 1662-5218
Editore: Frontiers Research Foundation
DOI: 10.3389/fnbot.2019.00098

Editorial: Intrinsically Motivated Open-Ended Learning in Autonomous Robots

Autori: Vieri Giuliano Santucci, Pierre-Yves Oudeyer, Andrew Barto, Gianluca Baldassarre
Pubblicato in: Frontiers in Neurorobotics, Numero 13, 2020, ISSN 1662-5218
Editore: Frontiers Research Foundation
DOI: 10.3389/fnbot.2019.00115

Development of body knowledge as measured by arm differentiation in infants: From global to local?

Autori: Lisa Jacquey, Sergiu Tcaci Popescu, Judith Vergne, Jacqueline Fagard, Rana Esseily, Kevin O’Regan
Pubblicato in: British Journal of Developmental Psychology, Numero 38/1, 2020, Pagina/e 108-124, ISSN 0261-510X
Editore: Wiley-Blackwell
DOI: 10.1111/bjdp.12309

Acceptability of the Transitional Wearable Companion “+me” in Children With Autism Spectrum Disorder: A Comparative Pilot Study

Autori: Valerio Sperati, Beste Özcan, Laura Romano, Tania Moretta, Simone Scaffaro, Noemi Faedda, Giada Turturo, Francesca Fioriello, Simone Pelosi, Federica Giovannone, Carla Sogos, Vincenzo Guidetti, Gianluca Baldassarre
Pubblicato in: Frontiers in Psychology, Numero 11, 2020, ISSN 1664-1078
Editore: Frontiers Research Foundation
DOI: 10.3389/fpsyg.2020.00951

Action observation and motor imagery for rehabilitation in Parkinson's disease: A systematic review and an integrative hypothesis

Autori: Daniele Caligiore, Magda Mustile, Gianfranco Spalletta, Gianluca Baldassarre
Pubblicato in: Neuroscience & Biobehavioral Reviews, Numero 72, 2017, Pagina/e 210-222, ISSN 0149-7634
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.neubiorev.2016.11.005

The architecture challenge: Future artificial-intelligence systems will require sophisticated architectures, and knowledge of the brain might guide their construction

Autori: Gianluca Baldassarre, Vieri Giuliano Santucci, Emilio Cartoni, Daniele Caligiore
Pubblicato in: Behavioral and Brain Sciences, Numero 40, 2017, ISSN 0140-525X
Editore: Cambridge University Press
DOI: 10.1017/S0140525X17000036

Which limb is it? Responses to vibrotactile stimulation in early infancy

Autori: Eszter Somogyi, Lisa Jacquey, Tobias Heed, Matej Hoffmann, Jeffrey J. Lockman, Lionel Granjon, Jacqueline Fagard, J. Kevin O'Regan
Pubblicato in: British Journal of Developmental Psychology, 2017, ISSN 0261-510X
Editore: Wiley-Blackwell
DOI: 10.1111/bjdp.12224

Know Your Body Through Intrinsic Goals

Autori: Francesco Mannella, Vieri G. Santucci, Eszter Somogyi, Lisa Jacquey, Kevin J. O'Regan, Gianluca Baldassarre
Pubblicato in: Frontiers in Neurorobotics, Numero 12, 2018, ISSN 1662-5218
Editore: Frontiers Research Foundation
DOI: 10.3389/fnbot.2018.00030

Acceptability of the Transitional Wearable Companion “+me” in Typical Children: A Pilot Study

Autori: Valerio Sperati, Beste Özcan, Laura Romano, Simone Scaffaro, Tania Moretta, Giada Turturo, Maria Nicoletta Aliberti, Vincenzo Guidetti, Gianluca Baldassarre
Pubblicato in: Frontiers in Psychology, Numero 10, 2019, ISSN 1664-1078
Editore: Frontiers Research Foundation
DOI: 10.3389/fpsyg.2019.00125

Action Observation With Dual Task for Improving Cognitive Abilities in Parkinson’s Disease: A Pilot Study

Autori: Daniele Caligiore, Magda Mustile, Alissa Fineschi, Laura Romano, Fabrizio Piras, Francesca Assogna, Francesco E. Pontieri, Gianfranco Spalletta, Gianluca Baldassarre
Pubblicato in: Frontiers in Systems Neuroscience, Numero 13, 2019, ISSN 1662-5137
Editore: Frontiers Research Foundation
DOI: 10.3389/fnsys.2019.00007

Bio-Inspired Model Learning Visual Goals and Attention Skills Through Contingencies and Intrinsic Motivations

Autori: Valerio Sperati, Gianluca Baldassarre
Pubblicato in: IEEE Transactions on Cognitive and Developmental Systems, Numero 10/2, 2018, Pagina/e 326-344, ISSN 2379-8920
Editore: IEEE
DOI: 10.1109/tcds.2017.2772908

Dysfunctions of the basal ganglia-cerebellar-thalamo-cortical system produce motor tics in Tourette syndrome

Autori: Daniele Caligiore, Francesco Mannella, Michael A. Arbib, Gianluca Baldassarre
Pubblicato in: PLOS Computational Biology, Numero 13/3, 2017, Pagina/e e1005395, ISSN 1553-7358
Editore: Public Library of Science
DOI: 10.1371/journal.pcbi.1005395

Fetal Origin of Sensorimotor Behavior

Autori: Jaqueline Fagard, Rana Esseily, Lisa Jacquey, Kevin O’Regan, Eszter Somogyi
Pubblicato in: Frontiers in Neurorobotics, Numero 12, 2018, ISSN 1662-5218
Editore: Frontiers Research Foundation
DOI: 10.3389/fnbot.2018.00023

Stage-Wise Learning of Reaching Using Little Prior Knowledge

Autori: François de La Bourdonnaye, Céline Teulière, Jochen Triesch, Thierry Chateau
Pubblicato in: Frontiers in Robotics and AI, Numero 5, 2018, ISSN 2296-9144
Editore: Frontiers
DOI: 10.3389/frobt.2018.00110

Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks

Autori: Daniel Tanneberg, Jan Peters, Elmar Rueckert
Pubblicato in: Neural Networks, Numero 109, 2019, Pagina/e 67-80, ISSN 0893-6080
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.neunet.2018.10.005

A Reinforcement Learning Architecture that Transfers Knowledge between Skills when Solving Multiple Tasks

Autori: Paolo Tommasino, Daniele Caligiore, Marco Mirolli, Gianluca Baldassarre
Pubblicato in: IEEE Transactions on Cognitive and Developmental Systems, 2019, Pagina/e 1-1, ISSN 2379-8920
Editore: IEEE
DOI: 10.1109/tcds.2016.2607018

Inverse reinforcement learning via nonparametric spatio-temporal subgoal modeling

Autori: A. Šošić, E. Rueckert, J. Peters, A. M. Zoubir, H. Koeppl
Pubblicato in: The Journal of Machine Learning Research, 2018, ISSN 1532-4435
Editore: MIT Press

Autonomous Development of Active Binocular and Motion Vision Through Active Efficient Coding

Autori: Alexander Lelais, Jonas Mahn, Vikram Narayan, Chong Zhang, Bertram E. Shi, Jochen Triesch
Pubblicato in: Frontiers in Neurorobotics, Numero 13, 2019, ISSN 1662-5218
Editore: Frontiers Research Foundation
DOI: 10.3389/fnbot.2019.00049

Robot End Effector Tracking Using Predictive Multisensory Integration

Autori: Lakshitha P. Wijesinghe, Jochen Triesch, Bertram E. Shi
Pubblicato in: Frontiers in Neurorobotics, Numero 12, 2018, ISSN 1662-5218
Editore: Frontiers Research Foundation
DOI: 10.3389/fnbot.2018.00066

An Embodied Agent Learning Affordances With Intrinsic Motivations and Solving Extrinsic Tasks With Attention and One-Step Planning

Autori: Gianluca Baldassarre, William Lord, Giovanni Granato, Vieri Giuliano Santucci
Pubblicato in: Frontiers in Neurorobotics, Numero 13, 2019, ISSN 1662-5218
Editore: Frontiers Research Foundation
DOI: 10.3389/fnbot.2019.00045

Different Dopaminergic Dysfunctions Underlying Parkinsonian Akinesia and Tremor

Autori: Daniele Caligiore, Francesco Mannella, Gianluca Baldassarre
Pubblicato in: Frontiers in Neuroscience, Numero 13, 2019, ISSN 1662-453X
Editore: Frontiers
DOI: 10.3389/fnins.2019.00550

A generative spiking neural-network model of goal-directed behaviour and one-step planning

Autori: Ruggero Basanisi, Andrea Brovelli, Emilio Cartoni, Gianluca Baldassarre
Pubblicato in: PLOS Computational Biology, Numero 16/12, 2020, Pagina/e e1007579, ISSN 1553-7358
Editore: Public Library Of Science
DOI: 10.1371/journal.pcbi.1007579

6-Month-Old Infants’ Sensitivity to Contingency in a Variant of the Mobile Paradigm With Proximal Stimulation Studied at Fine Temporal Resolution in the Laboratory

Autori: Sergiu Tcaci Popescu, Alice Dauphin, Judith Vergne, J. Kevin O’Regan
Pubblicato in: Frontiers in Psychology, Numero 12, 2021, ISSN 1664-1078
Editore: Frontiers Research Foundation
DOI: 10.3389/fpsyg.2021.610002

Développement du savoir-faire corporel durant la première année de vie du bébé

Autori: Lisa Jacquey, Jacqueline Fagard, Kevin O’Regan, Rana Esseily
Pubblicato in: Enfance, Numero N°2/2, 2020, Pagina/e 175, ISSN 0013-7545
Editore: Presses Universitaires de France
DOI: 10.3917/enf2.202.0175

A computational model of language functions in flexible goal-directed behaviour

Autori: Giovanni Granato, Anna M. Borghi, Gianluca Baldassarre
Pubblicato in: Scientific Reports, Numero 10/1, 2020, ISSN 2045-2322
Editore: Nature Publishing Group
DOI: 10.1038/s41598-020-78252-y

Evolutionary training and abstraction yields algorithmic generalization of neural computers

Autori: Daniel Tanneberg, Elmar Rueckert, Jan Peters
Pubblicato in: Nature Machine Intelligence, Numero 2/12, 2020, Pagina/e 753-763, ISSN 2522-5839
Editore: Springer
DOI: 10.1038/s42256-020-00255-1

Intrinsic motivations and open-ended learning

Autori: Baldassarre, Gianluca
Pubblicato in: Numero 13, 2019
Editore: arXiv

Recurrent Connectivity Aids Recognition of Partly Occluded Objects

Autori: Ernst, Markus Roland; Triesch, Jochen; Burwick, Thomas
Pubblicato in: Numero 1, 2019
Editore: arXiv

Learning High-Level Planning Symbols from Intrinsically Motivated Experience

Autori: Oddi, Angelo; Rasconi, Riccardo; Cartoni, Emilio; Sartor, Gabriele; Baldassarre, Gianluca; Santucci, Vieri Giuliano
Pubblicato in: Numero 3, 2019
Editore: arXiv

Autonomous learning of multiple, context-dependent tasks

Autori: Santucci, Vieri Giuliano; Montella, Davide; da Silva, Bruno Castro; Baldassarre, Gianluca
Pubblicato in: Numero 1, 2020
Editore: arXiv

Autonomous Open-Ended Learning of Interdependent Tasks

Autori: Santucci, Vieri Giuliano; Cartoni, Emilio; da Silva, Bruno Castro; Baldassarre, Gianluca
Pubblicato in: Numero 2, 2019
Editore: arXiv

ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows

Autori: Urain, Julen; Ginesi, Michelle; Tateo, Davide; Peters, Jan
Pubblicato in: Numero 12, 2020
Editore: arXiv

An open-ended learning architecture to face the REAL 2020 simulated robot competition

Autori: Cartoni, Emilio; Montella, Davide; Triesch, Jochen; Baldassarre, Gianluca
Pubblicato in: Numero 1, 2020
Editore: arXiv

The Development of Active Binocular Vision under Normal and Alternate Rearing Conditions

Autori: Lukas Klimmasch; Johann Schneider; Alexander Lelais; Bertram E. Shi; Jochen Triesch
Pubblicato in: Numero 1, 2020
Editore: BioRxiv
DOI: 10.1101/2020.02.20.957449

Learning Algorithmic Solutions to Symbolic Planning Tasks with a Neural Computer Architecture

Autori: Tanneberg, Daniel; Rueckert, Elmar; Peters, Jan
Pubblicato in: Numero 13, 2020
Editore: arXiv

Supervised Topological Maps

Autori: Mannella, Francesco
Pubblicato in: Numero 15, 2020
Editore: arXiv

Sensorimotor Contingencies as a Key Drive of Development: From Babies to Robots

Autori: Lisa Jacquey; Gianluca Baldassarre; Vieri Giuliano Santucci; J. Kevin O'Regan
Pubblicato in: https://hal.archives-ouvertes.fr/hal-03130944, Numero 1, 2019
Editore: PsyArXiv
DOI: 10.31234/osf.io/sr52x

Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders

Autori: Ernst, Markus Roland; Triesch, Jochen; Burwick, Thomas
Pubblicato in: Lecture Notes in Computer Science - Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing, Numero 1, 2019
Editore: arXiv

Advancing Trajectory Optimization with Approximate Inference: Exploration, Covariance Control and Adaptive Risk

Autori: Watson, Joe; Peters, Jan
Pubblicato in: Numero 1, 2021
Editore: arXiv

Optimal Options for Multi-Task Reinforcement Learning Under Time Constraints

Autori: Del Verme, Manuel; da Silva, Bruno Castro; Baldassarre, Gianluca
Pubblicato in: Numero 9, 2020
Editore: arXiv

Autonomous discovery of the goal space to learn a parameterized skill

Autori: E. Cartoni, G. Baldassarre
Pubblicato in: 2018
Editore: arXiv

Learning to touch objects through stage-wise deep reinforcement learning

Autori: de La Bourdonnaye , François; Teulière , Céline; Triesch , Jochen; Chateau , Thierry
Pubblicato in: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Numero 1, 2019
Editore: IEEE

Autonomous Reinforcement Learning of Multiple Interrelated Tasks

Autori: Santucci V. G., Baldassarre G. and Cartoni E.
Pubblicato in: arXiv, 2019
Editore: arXiv

Recurrent Connectivity Aids Recognition of Partly Occluded Objects

Autori: Ernst, Markus Roland and Triesch, Jochen and Burwick, Thomas
Pubblicato in: arXiv, 2019
Editore: Cornell University

Self-Calibrating Active Binocular Vision via Active Efficient Coding with Deep Autoencoders

Autori: Wilmot, Charles; Shi, Bertram E.; Triesch, Jochen
Pubblicato in: Numero 6, 2021
Editore: arXiv

Learning walk and trot from the same objective using different types of exploration

Autori: Liu, Zinan; Ploeger, Kai; Stark, Svenja; Rueckert, Elmar; Peters, Jan
Pubblicato in: Numero 11, 2019
Editore: arXiv

Learning Abstract Representations through Lossy Compression of Multi-Modal Signals

Autori: Wilmot, Charles; Triesch, Jochen
Pubblicato in: Numero 1, 2021
Editore: arXiv

Model-Based Quality-Diversity Search for Efficient Robot Learning

Autori: Keller, Leon; Tanneberg, Daniel; Stark, Svenja; Peters, Jan
Pubblicato in: Numero 13, 2020
Editore: arXiv

Advancing Trajectory Optimization with Approximate Inference: Exploration, Covariance Control and Adaptive Risk

Autori: Watson, Joe; Peters, Jan
Pubblicato in: arXiv, Numero 1, 2021
Editore: arXiv

SKID RAW: Skill Discovery From Raw Trajectories

Autori: Daniel Tanneberg, Kai Ploeger, Elmar Rueckert, Jan Peters
Pubblicato in: IEEE Robotics and Automation Letters, Numero 6/3, 2021, Pagina/e 4696-4703, ISSN 2377-3766
Editore: arXiv
DOI: 10.1109/lra.2021.3068891

Autonomous Reinforcement Learning of Multiple Interrelated Tasks

Autori: Vieri Giuliano Santucci, Gianluca Baldassarre, Emilio Cartoni
Pubblicato in: 2019 Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2019, Pagina/e 221-227, ISBN 978-1-5386-8128-2
Editore: IEEE
DOI: 10.1109/devlrn.2019.8850713

Local Online Motor Babbling: Learning Motor Abundance of a Musculoskeletal Robot Arm *

Autori: Zinan Liu, Arne Hitzmann, Shuhei Ikemoto, Svenja Stark, Jan Peters, Koh Hosoda
Pubblicato in: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019, Pagina/e 6594-6601, ISBN 978-1-7281-4004-9
Editore: IEEE
DOI: 10.1109/iros40897.2019.8967791

Intrinsically Motivated Discovered Outcomes Boost User’s Goals Achievement in a Humanoid Robot

Autori: Kristsana Seepanomwan, Vieri Giuliano Santucci, Gianluca, Baldassarre
Pubblicato in: Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2017 Joint IEEE International Conference on, 2017
Editore: IEEE

Workshop On Ethical Issues of Open Ended-Learning in Autonomous Robots

Autori: Daniele Caligiore, Vieri Giuliano Santucci, Gianluca Baldassarre
Pubblicato in: Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2017 Joint IEEE International Conference on, 2017
Editore: IEEE

Learning of Active Binocular Vision in a Biomechanical Model of the Oculomotor System

Autori: Lukas Klimmasch, Alexander Lelais, Alexander Lichtenstein, Bertram Emil Shi, Jochen Triesch
Pubblicato in: Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2017 Joint IEEE International Conference on, 2017
Editore: IEEE

Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals

Autori: Tanneberg D., Peters J., Rueckert E.
Pubblicato in: Proceedings of Machine Learning Research: Conference on Robot Learning (CoRL), 2017
Editore: PMLR

Learning Inverse Dynamics Models in O(n) time with LSTM networks

Autori: Rueckert E., Nakatenus M., Tosatto S., Peters, J
Pubblicato in: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017
Editore: IEEE

Efficient Online Adaptation with Stochastic Recurrent Neural Networks

Autori: Tanneberg D., Peters J., Rueckert E.
Pubblicato in: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017
Editore: IEEE

A Comparison of Distance Measures for Learning Nonparametric Motor Skill Libraries

Autori: Stark S., Peters J., Rueckert E.
Pubblicato in: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2017
Editore: IEEE

Simulation of the underactuated Sake Robotics Gripper in V-REP

Autori: Thiem S., Stark S., Tanneberg D., Peters J., Rueckert E.
Pubblicato in: Workshop at the International Conference on Humanoid Robots (HUMANOIDS), 2017
Editore: IEEE

Development of reaching to the body in early infancy: From experiments to robotic models

Autori: Matej Hoffmann, Lisa K. Chinn, Eszter Somogyi, Tobias Heed, Jacqueline Fagard, Jeffrey J. Lockman, J. Kevin O'Regan
Pubblicato in: 2017 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 2017, Pagina/e 112-119, ISBN 978-1-5386-3715-9
Editore: IEEE
DOI: 10.1109/devlrn.2017.8329795

Action-outcome contingencies as the engine of open-ended learning: computational models and developmental experiments

Autori: G. Baldassarre, F. Mannella, V.G. Santucci,E. Somogyi, L. Jacquey, M. Hamilton, J.K. O’Regan
Pubblicato in: Proceedings of The 8th IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob2018), 2018
Editore: IEEE

Learning to Categorize Bug Reports with LSTM Networks

Autori: K.D. Gondaliya, J. Peters, E. Rueckert
Pubblicato in: International Conference on Advances in System Testing and Validation Lifecycle, 2018
Editore: IARIA XPS Press

Experience Reuse with Probabilistic Movement Primitives

Autori: Svenja Stark, Jan Peters, Elmar Rueckert
Pubblicato in: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019, Pagina/e 1210-1217, ISBN 978-1-7281-4004-9
Editore: IEEE
DOI: 10.1109/iros40897.2019.8968545

La sensibilité aux contingences sensorimotrices chez le bébé et son rôle dans le développement du savoir-faire corporel. Approche croisée en robotique et psychologie du développement

Autori: Jacquey, Lisa
Pubblicato in: 2019
Editore: Université de Paris

Understand-Compute-Adapt: Neural Networks for Intelligent Agents

Autori: Tanneberg, Daniel
Pubblicato in: Numero 4, 2020
Editore: Technische Universität Darmstadt,
DOI: 10.25534/tuprints-00017234

Développement de la sensibilité aux contingences sensorimotrices lors des 6 premiers mois de vie

Autori: Fremond Claire
Pubblicato in: 2020
Editore: Master of Science and Technology, Sorbonne University

An Active Efficient Coding Model of Binocular Vision Development Under Normal and Abnormal Rearing Conditions

Autori: Lukas Klimmasch, Johann Schneider, Alexander Lelais, Bertram E. Shi, Jochen Triesch
Pubblicato in: From Animals to Animats 15 - 15th International Conference on Simulation of Adaptive Behavior, SAB 2018, Frankfurt/Main, Germany, August 14-17, 2018, Proceedings, Numero 10994, 2018, Pagina/e 66-77, ISBN 978-3-319-97627-3
Editore: Springer International Publishing
DOI: 10.1007/978-3-319-97628-0_6

The development of reaching and grasping: towards an integrated framework based on a critical review of computational and robotic models

Autori: D. Caligiore, G. Baldassarre
Pubblicato in: 2019
Editore: Taylor and Francis Group

Recurrent Connections Aid Occluded Object Recognition by Discounting Occluders

Autori: Markus Roland Ernst, Jochen Triesch, Thomas Burwick
Pubblicato in: Artificial Neural Networks and Machine Learning – ICANN 2019: Image Processing - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part III, Numero 11729, 2019, Pagina/e 294-305, ISBN 978-3-030-30507-9
Editore: Springer International Publishing
DOI: 10.1007/978-3-030-30508-6_24

Learning Hierarchical Integration of Foveal and Peripheral Vision for Vergence Control by Active Efficient Coding

Autori: Zhetuo Zhao, Jochen Triesch, Bertram E. Shi
Pubblicato in: From Animals to Animats 15 - 15th International Conference on Simulation of Adaptive Behavior, SAB 2018, Frankfurt/Main, Germany, August 14-17, 2018, Proceedings, Numero 10994, 2018, Pagina/e 78-89, ISBN 978-3-319-97627-3
Editore: Springer International Publishing
DOI: 10.1007/978-3-319-97628-0_7

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