IEEE Task Force on Evolutionary Developmental Systems and Robotics
IEEE Computational Intelligence Society (CIS) Technical Committee on
Cognitive and Developmental Systems (CDS)
Aim and Scope
The objective of this task force is to strengthen the links between
evolutionary approaches in artificial intelligence and the developmental and
cognitive systems community. There are many potential convergences and common
discussion topics, including, but not limited to:
- A large part of the evolutionary intelligence community work on
“Generative and Developmental Encoding” to evolve large, life-like neural
networks (“artificial brains”); as the name suggest it, these encoding exploit
developmental rules to make large neural networks that exhibit some features of
biological nervous systems like modularity, hierarchy, repetition, symmetry,
- A new trend in evolutionary intelligence is to study alternative
selective pressures and, in particular, selective pressures that encourage
exploration (novelty search, behavioral diversity, etc.); these techniques
share many objectives and ideas with the exploration algorithms studied in the
developmental robotics community (e.g. babbling).
- Evolution can be an effective metaphore to
explain and therefore imitate the plasticity of the brain (see neural darwinism and neural replicators).
- Evolution and life-time learning are two complementary processes that
interact at different scales and a key research avenue is to understand what
should be designed by evolution and what should be left for life-time learning.
Task Force Chair:
Jim Torresen, University of Oslo, Norway
Task Force Vice-Chairs:
Gusz Eiben, Vrije Universiteit Amsterdam, Netherlands
Doncieux, Sorbonne Université, France
Task Force Members:
Soltoggio, Loughborough University, UK
Clark, Missouri State
Emma Hart, Edinburgh Napier University, UK
M. Moore, Grand Valley State
Mouret, INRIA, France
Clune, University of
Wyoming/Uber AI Labs, US
Kyrre Glette, University of Oslo, Norway
Bredeche, Sorbonne Université, France
Sanaz Mostaghim, Otto von Guericke University Magdeburg, Germany
Risi, IT University of Copenhagen, Denmark
Nichele, Oslo Metropolitan University, Norway
§ Stephane Doncieux is involved in a IROS
2021 workshop entitled "New Horizons for Robot Learning and
common obstacles of result transfer to industry"
§ Jeff Clune will give the keynote Improving Robot and Deep
Reinforcement Learning via Quality Diversity, Open-Ended, and AI-Generating
Algorithms at CORL 2021 (November 8 – 11)
§ Kyrre Glette (together with Frank Veenstra) is planning to host a special session on
Evolutionary Robotics in EvoApplications 2022
§ Stephane Doncieux with Antoine Cully and
Jean-Baptiste Mouret will present a tutorial on QD
algorithms at GECCO 2021. 10–14 July, 2021. There will also be another relevant workshop at
the same conference: EvoRL – Evolutionary Reinforcement Learning Workshop organised by
§ Stefano Nichele (together with Giovanni Iacca and Eric Medvet) will
organise a Special Session on Bio-inspired Approaches for Modular Robotics at ALIFE
2021, 19-23 July, 2021
§ Jeff Clune gave a keynote at the ICLR 2021
Neural Architecture Search Workshop, 7 May 2021
§ Jim Torresen gave the tutorial "Ethical
Considerations in Robotics and Automation" at ICRA
§ Gusz Eiben (together with Andy Tyrrell and Emma
Hart) is a guest editors for a Special
Issue on Towards autonomous evolution, (re)production and learning in robotic
eco-systems, IEEE Transactions on Cognitive
and Developmental Systems
§ Kyrre Glette (together with David Howard and Nick
Cheney) is editing a Research Topic “Evolving
Robotic Morphologies” in Frontiers in Robotics and AI
§ EU projects in which evolutionary methods are used: SoftManBot and VeriDREAM (Stephane Doncieux reported)
§ Doncieux, S., Paolo, G., Laflaquière, A., & Coninx, A. (2020, June). Novelty search makes evolvability
inevitable. In Proceedings of the 2020 Genetic and Evolutionary
Computation Conference (pp. 85-93).
§ Jegorova, Marija, Stéphane Doncieux,
and Timothy M. Hospedales. "Behavioral
Repertoire via Generative Adversarial Policy Networks." IEEE
Transactions on Cognitive and Developmental Systems (2020).
§ Kim, S., Coninx, A., & Doncieux, S. (2021). From exploration to control: learning
object manipulation skills through novelty search and local
adaptation. Robotics and Autonomous Systems, 136, 103710.
§ Le Goff, L. K., Hart, E., Coninx, A., & Doncieux, S. (2020, July). On pros and cons of evolving
topologies with novelty search. In Artificial Life Conference
Proceedings (pp. 423-431). One Rogers Street, Cambridge, MA 02142-1209 USA
journals-info@ mit. edu:
§ J. Nordmoen, F. Veenstra,
K. O. Ellefsen, and K. Glette,
“MAP-Elites enables powerful stepping stones and diversity for modular robotics,” Frontiers in Robotics and AI, vol. 8, p. 56, 2021.
§ T. F. Nygaard, C. P. Martin, J. Torresen, K. Glette, and D. Howard, “Real-world embodied AI through a
morphologically adaptive quadruped robot,” Nature Machine Intelligence, vol. 3, no. 5, pp. 410–419, 2021.
§ T. F. Nygaard, C. P. Martin, D. Howard, J. Torresen,
and K. Glette, “Environmental adaptation of robot
morphology and control through real-world evolution,” Evolutionary Computation, 2021.
§ Paolo, G., Laflaquiere, A., Coninx, A., & Doncieux, S.
(2020, May). Unsupervised learning and exploration of reachable outcome space.
In 2020 IEEE International Conference on Robotics and Automation (ICRA) (pp. 2379-2385). IEEE.
§ Paolo, G., Coninx, A., Doncieux,
S., & Laflaquière, A. (2021). Sparse Reward
Exploration via Novelty Search and Emitters. arXiv
preprint arXiv:2102.03140. (accepted at GECCO 2021)
§ Salehi, Achkan, Alexandre Coninx, and
Stephane Doncieux. "BR-NS: an Archive-less
Approach to Novelty Search." arXiv preprint
arXiv:2104.03936 (2021). (accepted at GECCO 2021)
§ Stéphane Doncieux (together with Antoine
Cully and Jean-Baptiste Mouret) gave a tutorial at
GECCO 2020 on Quality-Diversity Optimization
§ Gusz Eiben (together with Emma Hart and David
Howard) organised a the
workshop "ADRR — Automated Design of Robots for
the Real-world" at GECCO 2020
§ Special issue of Congitive Neurosynamics (Springer) as follow up of the workshop we
organized at IEEE ICDL-EPIROB in Oslo. Link https://www.springer.com/journal/11571/updates/17312386
§ Special Issue (SI) on Development and Learning and on Epigenetic
Robotics in IEEE Transactions on Cognitive and Developmental Systems. SI with
extended versions of the best papers presented in the 2019 ICDL-EpiRob conference.
§ Stefano Nichele is co-chairing IEEE ALIFE at
IEEE SSCI 2020. Both “evolutionary developmental
systems” and robotics are within the scope. Link: http://www.ieeessci2020.org/symposiums/alife.html.
Location Canberra Australia, 1-4 December 2020.
§ Pontes-Filho, Sidney, Pedro Lind,
Anis Yazidi, Jianhua Zhang,
Hugo Hammer, Gustavo BM Mello,
Ioanna Sandvig, Gunnar Tufte, and Stefano Nichele. "EvoDynamic: A Framework for the Evolution of Generally
Represented Dynamical Systems and Its Application to Criticality." In
International Conference on the Applications of Evolutionary Computation (Part
of EvoStar), pp. 133-148. Springer, Cham, 2020. https://link.springer.com/chapter/10.1007/978-3-030-43722-0_9
§ K. Heiney, O. H. Ramstad, I. Sandvig, A. Sandvig and S. Nichele, "Assessment and manipulation of the
computational capacity of in vitro neuronal networks through criticality in
neuronal avalanches," 2019 IEEE Symposium Series on Computational
Intelligence (SSCI), Xiamen, China, 2019, pp.
247-254, doi: 10.1109/SSCI44817.2019.9002693. https://ieeexplore.ieee.org/document/9002693
§ Eseoghene Ben-Iwhiwhu, Pawel Ladosz,
Jeffery Dick, Wen-Hua Chen, Praveen Pilly, Andrea Soltoggio, "Evolving Inborn Knowledge For Fast Adaptation in Dynamic POMDP
Problems", accepted as a full paper at GECCO
§ Paul Ecoffet, Nicolas Bredeche,
Jean-Baptiste André. Nothing better to do? Environment
quality and the evolution of cooperation by partner choice. Preprint on Biorxiv: https://www.biorxiv.org/content/10.1101/2020.05.04.076141v1
§ Nicolas Fontbonne, Olivier Dauchot and
Nicolas Bredeche. Distributed On-line Learning in
Swarm Robotics with Limited Communication Bandwidth. Accepted at the Congress
on Evolutionary Computation (CEC), 2020. (PDF not yet online)
§ A. Duburcq, N. Bredeche,
Y. Chevaleyre. Online Trajectory Planning Through
Combined Trajectory Optimization and Function Approximation: Application to the
Exoskeleton Atalante. Accepted at the International Conference on Robotics and
Automation (ICRA), 2020. (PDF not yet online)
§ A. Bernard, N. Bredeche, J-B. Andre. Indirect
genetic effects allow to escape the inefficient equilibrium in a coordination
game. Evolution Letters, to appear in 2020. An earlier draft is available as
PDF on BioArxiv: https://www.biorxiv.org/content/early/2018/09/20/422287
- Jeff Clune,
Presidential Early Career Award for Scientists and Engineers (PECASE)
- Stéphane Doncieux, lectures a course at the International
Summer School on Intrinsically Motivated Open-Ended Learning (http://www.goal-robots.eu/announcements/events/summer-school-2019-2
Doncieux, "Open-ended learning in
robotics", talk at the IMOL 2019
- 9th Joint IEEE International Conference on Development and Learning
and on Epigenetic Robotics.
August 19-22, 2019 in Oslo, Norway. Paper submission deadline 22 February, 2019. Early registration deadline June 15,
Doncieux and Sebastian Risi
will co-chair the complex systems track at GECCO
Bredeche, Jean-Baptiste Mouret
and Stéphane Doncieu will give a tutorial on ER
at GECCO 2019.
- Gusz Eiben and Kyrre Glette are robotics area chairs for EvoApplications 2019, http://www.evostar.org/2019/cfp_evoapps.php
- McAllister R, Kahn G,
Clune J, Levine S (2019) Robustness to Out-of-Distribution Inputs via Task-Aware Generative
Conference on Robotics and Automation (ICRA). (pdf)
KO, Clune J, Lehman J, Miikkulainen R (2019) Designing Neural Networks through Neuroevolution. Nature Machine Intelligence, 1:1, 24-35. (pdf)
- Miconi T,
Rawal A, Clune J, Stanley KO (2019) Backpropamine: training self-modifying
neural networks with differentiable neuromodulated plasticity. International Conference on Learning Systems (ICLR)
(31% acceptance rate).
S., and Laflaquiere, A. and Coninx,
A. (2019) Novelty Search: a Theoretical Perspective, to appear in
- Alex Alcocer (OsloMet) chaired
the Autonomy Day 2018 – 2nd Workshop on Autonomous and Adaptive Systems, 3 May in Oslo, Norway including talks on
Doncieux, Joshua Auerbach, Richard Duro and Harold P. de Vladar
organized the workshop "Evolution in Cognition" at the GECCO conference in 2018, see https://sites.google.com/champlain.edu/eic2018/ .
Doncieux organised a
workshop on cognitive and developmental robotics at Sorbonne University,
the 19th of April 2018 (with Verena Hafner, Jose Santos Victor, Gianluca
Baldassare, Emre Ugur, Raja Chatila
and Doncieux as speakers)
Doncieux has also organized a research topic in
Frontiers, see https://www.frontiersin.org/research-topics/4233/evolvability-environments-embodiment-emergence-in-robotics.
Doncieux organised an
exhibition at the Palais de la Découverte from
March to May 2018 (the link with some informations
about that in French: http://www.palais-decouverte.fr/fr/ressources/docs-1chercheur1manip/des-robots-qui-apprennent/).
2018: Tutorial on Evolutionary Robotics at GECCO
2018 N. Bredeche, S. Doncieux
and J-B. Mouret.
Doncieux has given several talks about the DREAM
project in different contexts (7 in 2018 for academics and 4 for the
general public, with an audience varying between 20 people and more than
- Kyrre Glette co-chaired the EvoROBOT
track at EvoApplications 2018, http://www.evostar.org/2018/cfp_evorobot.php
showing the DyRET robot at the University of
Oslo and some outdoor experiments. Nbcnews.com, 25 June
Tønnes Nygaard at the University of Oslo about
the DyRET robot and evolutionary robotics. Digitaltrends.com,
23. may 2018
with Tønnes Nygaard about the DyRET robot and work developing it at the University
of Oslo. Wired.com, 18. may 2018
Learning: A Conceptual Framework Based on Representational
Redescription": https://loop.frontiersin.org/publications/51950747, A paper from the DREAM project consortium
about a formalisation of open-ended learning (in
which evolutionary approaches are relevant)
Q-Learning for robotics from Neuro-Evolution Results": https://ieeexplore.ieee.org/abstract/document/7879193, This is one instance of the formalisation described in the paper above: The
authors start with evolution to generate examples out of which we can
extract a representation that will allow to generalize and learn faster.
O. Stanley, Jeff Clune, Welcoming the Era of Deep Neuroevolution
- Tønnes F. Nygaard, Charles P. Martin, Eivind
Samuelsen, Jim Torresen, Kyrre Glette.Real-World Evolution Adapts Robot Morphology and Control to Hardware
Limitations. In GECCO18 (ACM), 2018.
- Tønnes F.
Nygaard, Charles P. Martin, Jim Torresen, Kyrre Glette. Self-Modifying Morphology Experiments with DyRET:
Dynamic Robot for Embodied Testing. Preprint: Arxiv,
- Tønnes F.
Nygaard, Charles P. Martin, Jim Torresen, Kyrre Glette. Exploring Mechanically Self-Reconfiguring Robots for Autonomous
Design. In Workshop on Autonomous Robot Design at ICRA18, 2018
A, Stanley, K. O., Risi, S., Born to Learn: the Inspiration, Progress, and Future of Evolved
Plastic Neural Networks. Neural Networks (2018) DOI: 10.1016/j.neunet.2018.07.013
C, Clune J (2018) Deep curiosity search: Intra-life exploration improves performance
on challenging deep reinforcement problems. NIPS Deep Reinforcement Learning Workshop. (pdf)
J, Chen J, Clune J, Stanley KO (2018) Safe mutations for deep and recurrent neural networks through
output gradients. Proceedings of the
Genetic and Evolutionary Computation Conference (GECCO).
E, Madhavan V, Such FP, Lehman J, Stanley KO,
Clune J (2018) Improving exploration in evolution strategies for deep
reinforcement learning via a population of novelty-seeking agents. Advances in Neural Information Processing
Systems (NIPS) 32 (20% acceptance rate). (pdf)
J, Chen J, Clune J, Stanley KO (2018) ES is more than just a traditional finite-difference approximator. Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO). (pdf)
- Miconi T,
Clune J, Stanley KO (2018) Differentiable plasticity: Training plastic neural networks with
backpropagation. ICML. (pdf)
FP, Madhavan V, Conti E, Lehman J, Stanley KO,
Clune J (2018) Deep neuroevolution: Genetic algorithms
are a competitive alternative for training deep neural networks for
reinforcement learning. NIPS Deep Reinforcement Learning Workshop. (pdf)
MS, Nguyen A, Kosmala M, Swanson A, Palmer M,
Parker C, Clune J (2018) Automatically identifying, counting, and describing wild animals in
camera-trap images with deep learning.
Proceedings of the National Academy of Sciences Vol. 115 no. 25. (pdf) (html) (featured on the cover)
- Stefano Nichele chaired the Workshop on Autonomous and Adaptive Systems, 11 May in Oslo including talks on ER.
2017: Nicolas Bredèche Tutorial chair at ECAL 2017
2017: Proceedings of the Fourteenth European Conference Artificial Life, ECAL 2017 (MIT Press 2017, ISBN 978-0-262-34633-7).
Editors: Carole Knibbe, Guillaume Beslon, David P. Parsons, Dusan
Misevic, Jonathan Rouzaud-Cornabas,
Nicolas Bredèche, Salima
Hassas, Olivier Simonin,
2017: Workshop on evolving physical systems at ECAL
2017. Organizers: John Rieffel, Jean-Baptiste Mouret, Nicolas Bredèche,
2017: Workshop on evolving collective behaviors in robotics at GECCO 2017, Organizers: N. Bredeche,
E. Haasdijk, A. Prieto and H. Hamman.
2017: Tutorial on Evolutionary Robotics at GECCO
2017. Organizers: N. Bredeche, S. Doncieux and J-B. Mouret.
2017: special issue on evolving physical systems of ALIFE journal (MIT
John Rieffel, Jean-Baptiste Mouret,
Nicolas Bredèche, Evert Haasdijk
- Sept.2016: Tutorial
chair at PPSN 2016. chairs: N. Bredeche and Carola Doerr
- Stéphane Doncieux initiated a dialogue on “Representational redescription in humans and machines”, in the
IEEE CIS Newsletter on CDS, 12(1).
- JB Mouret, J Clune, A. Cully and D. Tarapore
published a milestone article in Nature: Cully, A., Clune, J., Tarapore, D., & Mouret,
J. B. (2015). Robots that
can adapt like
animals1. Nature, 521 (7553), 503-507.
2015: Sebastian Risi and Jean-Baptiste Mouret are co-chairing the “Generative and Developmental Systems” track a GECCO’2015 (Madrid)
2015: Sebastian Risi was local chair or Evostar 2015 conference in Copenhagen, Denmark.
Mouret, Nicolas Bredeche
and Stéphane Doncieux presented a 3-hour
tutorial about Evolutionary Robotics at GECCO
2015 (Madrid, Spain) and ECAL 2015 (York, UK)
Risi will do a lecture about “Bio-inspired,
Automated Design of Machine Bodies and Artificial Brains” at for the Czech
European Robotics Week (Prague, November 2015).
2015: Tutorial on Evolutionary Robotics at GECCO
2015 and at ECAL 2015. Organizers: N. Bredeche,
S. Doncieux and J-B. Mouret.
2015: Fourth workshop on Evolving Physical Systems at ECAL
2015. Organizers: John Rieffel, Jean-Baptiste Mouret, Nicolas Bredèche,
2015: First workshop on Evolving Collective Behaviours
for Robotics at GECCO 2015. Organizers: N. Bredeche,
A. Prieto and E. Haasdijk.