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All Outputs (8)

Morpho-evolution with learning using a controller archive as an inheritance mechanism (2022)
Journal Article
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., Timmis, J., & Tyrrell, A. M. (2023). 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

Most work in evolutionary robotics centres on evolving a controller for a fixed body-plan. However, previous studiessuggest that simultaneously evolving both controller and body-plan could open up many interesting possibilities. However... Read More about Morpho-evolution with learning using a controller archive as an inheritance mechanism.

Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning (2021)
Journal Article
Hart, E., & Le Goff, L. K. (2022). Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning. Philosophical Transactions B: Biological Sciences, 377(1843), https://doi.org/10.1098/rstb.2021.0117

We survey and reflect on evolutionary approaches to the joint optimisation of the body and control of a robot, in scenarios where a the goal is to find a design that maximises performance on a specified task. The review is grounded in a general frame... Read More about Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning.

On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme (2021)
Presentation / Conference Contribution
Goff, L. K. L., & Hart, E. (2021, July). On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme. Presented at GECCO '21: Genetic and Evolutionary Computation Conference, Lille, France

We investigate a hierarchical scheme for the joint optimisation of robot bodies and controllers in a complex morphological space. An evolutionary algorithm optimises body-plans while a separate learning algorithm is applied to each body generated to... Read More about On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme.

Evolution of Diverse, Manufacturable Robot Body Plans (2020)
Presentation / Conference Contribution
Buchanan, E., Le Goff, L., Hart, E., Eiben, A. E., De Carlo, M., Li, W., Hale, M. F., Angus, M., Woolley, R., Winfield, A. F., Timmis, J., & Tyrrell, A. M. (2020, December). Evolution of Diverse, Manufacturable Robot Body Plans. Presented at International Conference on Evolvable Systems (ICES), Canberra, Australia

Advances in rapid prototyping have opened up new avenues of research within Evolutionary Robotics in which not only controllers but also the body plans (morphologies) of robots can evolve in real-time and real-space. However, this also introduces new... Read More about Evolution of Diverse, Manufacturable Robot Body Plans.

Hardware Design for Autonomous Robot Evolution (2020)
Presentation / Conference Contribution
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., Eiben, A. E., & Tyrrell, A. M. (2020, December). Hardware Design for Autonomous Robot Evolution. Presented at International Conference on Evolvable Hardware, Canberra Australia

The long term goal of the Autonomous Robot Evolution (ARE) project is to create populations of physical robots, in which both the controllers and body plans are evolved. The transition for evolutionary designs from purely simulation environments into... Read More about Hardware Design for Autonomous Robot Evolution.

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

A long-term vision of evolutionary robotics is a technology enabling the evolution of entire autonomous robotic ecosystems that live and work for long periods in challenging and dynamic environments without the need for direct human oversight. Evolut... Read More about Bootstrapping artificial evolution to design robots for autonomous fabrication.

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

Novelty search was proposed as a means of circumventing deception and providing selective pressure towards novel behaviours to provide a path towards open-ended evolution. Initial implementations relied on neuro-evolution approaches which increased n... Read More about On Pros and Cons of Evolving Topologies with Novelty Search.

Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation (2020)
Presentation / Conference Contribution
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., Hale, M. F., Angus, M., Woolley, R., Timmis, J., Winfield, A., & Tyrrell, A. M. (2020, July). Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation. Presented at ALife 2020, Online

In evolutionary robot systems where morphologies and controllers of real robots are simultaneously evolved, it is clear that there is likely to be requirements to refine the inherited controller of a 'newborn' robot in order to better align it to its... Read More about Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation.