Leni K. Le Goff, Ph.D.

Leni K. Le Goff, Ph.D.

Passionate about the mystery of the emergence of intelligence in living beings, Leni K. Le Goff research focuses on artificial evolution and developmental learning applied to robotics.

Publications

Arza, E., Le Goff, L. K., & Hart, E. (2024). Generalized Early Stopping in Evolutionary Direct Policy Search. ACM Transactions on Evolutionary Learning. https://doi.org/10.1145/3653024

Buchanan, E., Le Goff, L. K., Hale, M. F., Hart, E., Eiben, A. E., De Carlo, M., Angus, M., Woolley, R., Timmis, J., Winfield, A. F., et al. (2024). Towards a Unified Framework for Software-Hardware Integration in Evolutionary Robotics. Robotics, 13(11), 157. https://doi.org/10.3390/robotics13110157

Le Goff, L. K., & Smith, S. C. (2024). Efficient and Diverse Generative Robot Designs using Evolution and Intrinsic Motivation. arXiv. https://doi.org/10.48550/ARXIV.2411.18423

Le Goff, L., & Hart, E. (2024). Improving Efficiency of Evolving Robot Designs via Self-Adaptive Learning Cycles and an Asynchronous Architecture. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1607–1615. https://doi.org/10.1145/3638530.3664116

Thomson, S. L., Le Goff, L., Hart, E., & Buchanan, E. (2024). Understanding fitness landscapes in morpho-evolution via local optima networks. Proceedings of the Genetic and Evolutionary Computation Conference, 114–123. https://doi.org/10.1145/3638529.3654059

Le Goff, L. K., Buchanan, E., & Hart, E. (2024). An Investigation of the Factors Influencing Evolutionary Dynamics in the Joint Evolution of Robot Body and Control. arXiv. https://doi.org/10.48550/arXiv.2403.10303

Angus, M., Buchanan, E., Le Goff, L. K., Hart, E., Eiben, A. E., De Carlo, M., Winfield, A. F., Hale, M. F., Woolley, R., Timmis, J., et al. (2023). Practical hardware for evolvable robots. Frontiers in Robotics and AI, 10, 1206055. https://doi.org/10.3389/frobt.2023.1206055

Li, W., Buchanan, E., Le Goff, L. K., Hart, E., Hale, M. F., Wei, B., De Carlo, M., Angus, M., Woolley, R., Gan, Z., et al. (2023). Evaluation of frameworks that combine evolution and learning to design robots in complex morphological spaces. IEEE Transactions on Evolutionary Computation, 28(6), 1561–1574. https://doi.org/10.1109/TEVC.2023.3316363

Hart, E., & Le Goff, L. K. (2022). Artificial evolution of robot bodies and control: On the interaction between evolution, learning and culture. Philosophical Transactions of the Royal Society B, 377. https://doi.org/10.1098/rstb.2021.0117

Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., Winfield, A. F., Hale, M. F., Woolley, R., Angus, M., et al. (2022). Morpho evolution with learning using a controller archive as an inheritance mechanism. IEEE Transactions on Cognitive and Developmental Systems, 15(2), 507–517. https://doi.org/10.1109/TCDS.2022.3148543

Le Goff, L. K., Yaakoubi, O., Coninx, A., & Doncieux, S. (2022). Building an affordances map with interactive perception. Frontiers in Neurorobotics, 16, 504459. https://doi.org/10.3389/fnbot.2022.504459

Le Goff, L. K. L., & Hart, E. (2021). On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1498–1502. https://doi.org/10.1145/3449726.3463156

Buchanan, E., Le Goff, L. K., Hart, E., Eiben, A. E., De Carlo, M., Li, W., Hale, M. F., Angus, M., Woolley, R., Winfield, A. F., et al. (2020). Evolution of diverse, manufacturable robot body plans. 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2132–2139. https://doi.org/10.1109/SSCI47803.2020.9308434

Buchanan, E., Le Goff, L. K., Li, W., Hart, E., Eiben, A. E., De Carlo, M., Winfield, A. F., Hale, M. F., Woolley, R., Angus, M., et al. (2020). Bootstrapping artificial evolution to design robots for autonomous fabrication. Robotics, 9(4), 106. https://doi.org/10.3390/robotics9040106

Hale, M. F., Angus, M., Buchanan, E., Li, W., Woolley, R., Le Goff, L. K., De Carlo, M., Timmis, J., Winfield, A. F., Hart, E., et al. (2020). Hardware design for autonomous robot evolution. 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2140–2147. https://doi.org/10.1109/SSCI47803.2020.9308204

Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., Carlo, M. de, Hale, M. F., Angus, M., Woolley, R., Timmis, J., Winfield, A., & Tyrrell, A. M. (2020). Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation. 432–440. https://doi.org/10.1162/isal_a_00299

Le Goff, L. K., Hart, E., Coninx, A., & Doncieux, S. (2020). On Pros and Cons of Evolving Topologies with Novelty Search. The 2020 Conference on Artificial Life, 423–431. https://doi.org/10.1162/isal_a_00291

Lehman, J., Clune, J., Misevic, D., Adami, C., Altenberg, L., Beaulieu, J., Bentley, P. J., Bernard, S., Beslon, G., Bryson, D. M., et al. (2020). The surprising creativity of digital evolution: A collection of anecdotes from the evolutionary computation and artificial life research communities. Artificial Life, 26(2), 274–306. https://doi.org/10.1162/artl_a_00319

Doncieux, S., Bredeche, N., Goff, L. L., Girard, B., Coninx, A., Sigaud, O., Khamassi, M., Díaz-Rodríguez, N., Filliat, D., Hospedales, T., Eiben, A., & Duro, R. (2020). DREAM Architecture: A Developmental Approach to Open-Ended Learning in Robotics. arXiv. https://doi.org/10.48550/arXiv.2005.06223

Le Goff, L. K., Mukhtar, G., Coninx, A., & Doncieux, S. (2019). Bootstrapping Robotic Ecological Perception from a Limited Set of Hypotheses Through Interactive Perception. arXiv. https://doi.org/10.48550/ARXIV.1901.10968

Le Goff, L. K., Mukhtar, G., Le Fur, P.-H., & Doncieux, S. (2017). Segmenting objects through an autonomous agnostic exploration conducted by a robot. 2017 First IEEE International Conference on Robotic Computing (IRC), 284–291. https://doi.org/10.1109/IRC.2017.22

Le Goff, L. K., Le Fur, P.-H., & Doncieux, S. (2016). Exploration of unknown dynamic environments: A visual saliency-based babbling approach. 2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), 152–153. https://doi.org/10.1109/DEVLRN.2016.7846808

Le Goff, L., Maestre, C., & Doncieux, S. (2015). Visual saliency-based babbling of unknown dynamic environments. Proceedings of the Workshop Learning Object Affordances, IROS 2015, 1–2. https://hal.science/hal-02987424

Parutto, P., Le Goff, L., Léger, H., Mercy, G., Kouwe, E. van der, Chhun, A., Baudu, B., Guillocheau, G., Amiot, F., Ujéda, L., et al. (2014). Characterization and modeling of an iron-sensitive system in Escherichia coli. Advances in Systems and Synthetic Biology.