  Drawing on the idea that brain development is a Darwinian process of
``evolution + selection'' and the idea that the current state is a local
equilibrium state of many bodies with self-organization and evolution processes
driven by the temperature and gravity in our universe, in this work, we
describe an artificial intelligence system called the ``Synergetic Learning
Systems''. The system is composed of two or more subsystems (models, agents or
virtual bodies), and it is an open complex giant system. Inspired by natural
intelligence, the system achieves intelligent information processing and
decision-making in a given environment through cooperative/competitive
synergetic learning. The intelligence evolved by the natural law of ``it is not
the strongest of the species that survives, but the one most responsive to
change,'' while an artificial intelligence system should adopt the law of
``human selection'' in the evolution process. Therefore, we expect that the
proposed system architecture can also be adapted in human-machine synergy or
multi-agent synergetic systems. It is also expected that under our design
criteria, the proposed system will eventually achieve artificial general
intelligence through long term coevolution.
