Neuroevolution is a promising learning method in tasks with extremely large state and action spaces and hidden states. Recent advances allow neuroevolution to take place in real t...
Chern Han Yong, Kenneth O. Stanley, Risto Miikkula...
Previous work in knowledge transfer in machine learning has been restricted to tasks in a single domain. However, evidence from psychology and neuroscience suggests that humans ar...
Evolving recurrent neural networks for behavior control of robots equipped with larger sets of sensors and actuators is difficult due to the large search spaces that come with the ...
Software systems embed in them knowledge about the domain in which they operate. However, this knowledge is “latent”. Making such knowledge accessible could be of great value ...