Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation
Conference Proceeding
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., …Tyrrell, A. M. (2020)
Sample and time efficient policy learning with CMA-ES and Bayesian Optimisation. In ALIFE 2020: The 2020 Conference on Artificial Life. , (432-440). https://doi.org/10.1162/isal_a_00299
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 i...
On Pros and Cons of Evolving Topologies with Novelty Search
Conference Proceeding
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. Ini...