A study of GasNet spatial embedding in a delayed-response task

摘要

GasNet artificial neural networks can be used as complex neurocontrollers involving virtual chemical neuromodulation as well as synaptic interaction. The aim of this paper is to further explore the role of space in GasNet models on a delayed-response robot task. Comparative results demonstrate that the use of spatial constraints is not a prerequisite for a good performance of the original model in terms of speed of evolution.