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...
In this paper, we aim to design decision-making mechanisms for a simulated Khepera robot equipped with simple sensors, which integrates over time its perceptual experience in order...
This paper discusses an ontology based language modeling text mining approach to the annotation of protein community. Communities appear to play an important role in the functional...
Xiaodan Zhang, Daniel Duanqing Wu, Xiaohua Zhou, X...
The dynamics of the learning equation, which describes the evolution of the synaptic weights, is derived in the situation where the network contains recurrent connections. The deri...
Anthony N. Burkitt, Matthieu Gilson, J. Leo van He...
— Despite their success as optimization methods, evolutionary algorithms face many difficulties to design artifacts with complex structures. According to paleontologists, living...