Qadeer Ahmad
ABSTRACT
In this paper, we propose a scheme for evolving multiple-input-multiple-output (MIMO) artificial neural networks (ANNs) using grammatical evolution (GE). GE is a well-known technique for program evolution. While it has also been used for the evolution of ANN structures in the past, little work is reported on the evolution of MIMO ANNs.
MIMO ANNs are important for problems that have multiple outputs. Examples are controllers for autonomous systems such as unmanned aerial vehicles (UAVs) and driver-less cars that take in multiple inputs and are expected to produce multiple outputs simultaneously such as speed, steering etc. Certain regression problems are also MIMO in nature. Our results are promising.
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