  In this paper, we are introducing a novel model of artificial intelligence,
the functional neural network for modeling of human decision-making processes.
This neural network is composed of multiple artificial neurons racing in the
network. Each of these neurons has a similar structure programmed independently
by the users and composed of an intention wheel, a motor core and a sensory
core representing the user itself and racing at a specific velocity. The
mathematics of the neuron's formulation and the racing mechanism of multiple
nodes in the network will be discussed, and the group decision process with
fuzzy logic and the transformation of these conceptual methods into practical
methods of simulation and in operations will be developed. Eventually, we will
describe some possible future research directions in the fields of finance,
education and medicine including the opportunity to design an intelligent
learning agent with application in business operations supervision. We believe
that this functional neural network has a promising potential to transform the
way we can compute decision-making and lead to a new generation of neuromorphic
chips for seamless human-machine interactions.
