Computational Intelligence algorithms have gained a lot of attention of researchers in the recent years due to their ability to deliver near optimal solutions. In this paper we propose a new hierarchy which classifies algorithms based on their sources of inspiration. The algorithms have been divided into two broad domains namely modeling of human mind and nature inspired intelligence. Algorithms of Modeling of human mind take their motivation from the manner in which humans perceive and deal with information. Similarly algorithms of nature inspired intelligence domain are based on ordinary phenomenon occurring in nature. The latter has further been broken into swarm intelligence, geosciences and artificial immune system. Geoscience based is the new domain whose algorithms are based on geographic phenomenon on the Earths surface. A comprehensive tabular comparison is done amongst algorithms in each domain in various attributes such as problem solving method, application, characteristics and more. For further insights, we examine a variant of every algorithm and its implementation for a specific application. To understand the performance and efficiency better, we compare the performance of select algorithms on Traveling salesman problem. Brief Review of Computational Intelligence Algorithms