Abstract: This paper gives a survey of the background, intention, contents, and methodological peculiarities of Computational Intelligence （CI）, one of the flourishing advanced R ＆ D area. The essential differences and associations between CI and the traditional AI are discussed as well. It is argued that the main CI algorithms, such as the training algorithms for neural networks, the genetic algorithms, the evolutionary algorithms, and so on, should be considered as a category of quasi meta algorithm. They are especially good for solving problems that are very hard, if not impossible at all, to have deterministic mathematical or logic models. An ecological model of evolutionary computation and a general algorithm are also proposed and discussed. The application principles and perspectives of CI+AI hybrid synergetic computing systems in analyzing non linear, stochastic, dynamic or chaos systems, such as the trend analysis of the market pricing, solving NP hard problems, etc., are further discussed with sample examples.