This paper investigates evolvability of artificial neural networks within an artificial life environment. Five different structural mutations are investigated, including adaptive e...
Ehud Schlessinger, Peter J. Bentley, R. Beau Lotto
This case study demonstrates how the synthesis and the analysis of minimal recurrent neural robot control provide insights into the exploration of embodiment. By using structural e...
In the eld of arti cial evolution creating methods to evolve neural networks is an important goal. But how to encode the structure and properties of the neural network in the geno...
It is well known that incremental learning can often be difficult for traditional neural network systems, due to newly learned information interfering with previously learned infor...
Abstract. We present a system for automatically evolving neural networks as physics-based locomotion controllers for humanoid characters. Our approach provides two key features: (a...