Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity
Journal Article
Allard, M., Smith, S. C., Chatzilygeroudis, K., Lim, B., & Cully, A. (2023)
Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity. ACM Transactions on Evolutionary Learning and Optimization, 3(2), Article 6. https://doi.org/10.1145/3596912
In real-world environments, robots need to be resilient to damages and robust to unforeseen scenarios. Quality-Diversity (QD) algorithms have been successfully used to make ro...
Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning
Presentation / Conference Contribution
Flageat, M., Lim, B., Grillotti, L., Allard, M., Smith, S. C., & Cully, A. (2022, July)
Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning. Paper presented at Gecco 2022, Boston, Massachusetts
We present a Quality-Diversity benchmark suite for Deep Neuroevolution in Reinforcement Learning domains for robot control. The suite includes the definition of tasks, environ...
Hierarchical quality-diversity for online damage recovery
Presentation / Conference Contribution
Allard, M., Smith, S. C., Chatzilygeroudis, K., & Cully, A. (2022, June)
Hierarchical quality-diversity for online damage recovery. Presented at GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts
Adaptation capabilities, like damage recovery, are crucial for the deployment of robots in complex environments. Several works have demonstrated that using repertoires of pre-...
Self-Explainable Robots in Remote Environments
Presentation / Conference Contribution
Chiyah Garcia, F. J., Smith, S. C., Lopes, J., Ramamoorthy, S., & Hastie, H. (2021, March)
Self-Explainable Robots in Remote Environments. Presented at HRI '21: ACM/IEEE International Conference on Human-Robot Interaction, Boulder, Colorado
As robots and autonomous systems become more adept at handling complex scenarios, their underlying mechanisms also become increasingly complex and opaque. This lack of transpa...
Counterfactual Explanation and Causal Inference In Service of Robustness in Robot Control
Presentation / Conference Contribution
Smith, S. C., & Ramamoorthy, S. (2020, October)
Counterfactual Explanation and Causal Inference In Service of Robustness in Robot Control. Presented at 10th Joint IEEE International Conference on Development and Learning and Epigenetic Robotics 2020 - Virtual conference, Chile, Valparaiso, Chile
We propose an architecture for training generative models of counterfactual conditionals of the form, `can we modify event A to cause B instead of C?', motivated by applicatio...
Decoupled Sampling-Based Motion Planning for Multiple Autonomous Marine Vehicles
Presentation / Conference Contribution
Volpi, N. C., Smith, S. C., Pascoal, A. M., Simetti, E., Turetta, A., Alibani, M., & Polani, D. (2018, October)
Decoupled Sampling-Based Motion Planning for Multiple Autonomous Marine Vehicles. Presented at OCEANS 2018 MTS/IEEE Charleston, Charleston, SC
There is increasing interest in the deployment and operation of multiple autonomous marine vehicles (AMVs) for a number of challenging scientific and commercial operational mi...
Evaluation of Internal Models in Autonomous Learning
Journal Article
Smith, S. C., & Herrmann, J. M. (2019)
Evaluation of Internal Models in Autonomous Learning. IEEE Transactions on Cognitive and Developmental Systems, 11(4), 463-472. https://doi.org/10.1109/tcds.2018.2865999
Internal models (IMs) can represent relations between sensors and actuators in natural and artificial agents. In autonomous robots, the adaptation of IMs and the adaptation of...
Homeokinetic Reinforcement Learning
Presentation / Conference Contribution
Smith, S. C., & Herrmann, J. M. (2011, September)
Homeokinetic Reinforcement Learning. Presented at First IAPR TC3 Workshop, PSL 2011, Ulm, Germany
In order to find a control policy for an autonomous robot by reinforcement learning, the utility of a behaviour can be revealed locally through a modulation of the motor comma...
Clustering-Based Searching and Navigation in an Online News Source
Presentation / Conference Contribution
Smith, S. C., & Rodr铆guez, M. A. (2006, April)
Clustering-Based Searching and Navigation in an Online News Source. Presented at 28th European Conference on IR Research, ECIR 2006, London, UK
The growing amount of online news posted on the WWW demands new algorithms that support topic detection, search, and navigation of news documents. This work presents an algori...