Bipedalism is theorised to have emerged in humans in order to enable endurance running and tool use via the hands. It is one of the most complex styles of locomotion, with agents typically having a high center of mass and two feet very close together... Read More about Neuroevolution of bipedal locomotion: algorithmic, balance penalty and morphological improvements for improved robustness and performance.
All Outputs (2)
Evolving developmental, recurrent and convolutional neural networks for deliberate motion planning in sparse reward tasks (2020)
Thesis
Motion planning algorithms have seen a diverse set of approaches in a variety of disciplines. In the domain of artificial evolutionary systems, motion planning has been included in models to achieve sophisticated deliberate behaviours. These algorith... Read More about Evolving developmental, recurrent and convolutional neural networks for deliberate motion planning in sparse reward tasks.