This volume extends the complexity approach to economics. This complexity approach is not a completely new way of doing economics, and that it is a replacement for existing economics, but rather the integration of some new analytic and computational techniques into economists' bag of tools. It provides some alternative pattern generators, which can supplement existing approaches by providing an alternative way of finding patterns than be obtained by the traditional scientific approach. On this new kind of policy hints can be obtained. The reason why the complexity approach is taking hold now in economics is because the computing technology has advanced. This advance allows consideration of analytical systems that could not previously be considered by economists. Consideration of these systems suggested that the results of the "control-based" models might not extend easily to more complicated systems, and that we now have a method - piggybacking computer assisted analysis onto analytic methods - to start generating patterns that might provide a supplement to the standard approach. It is that approach that we consider the complexity approach. The papers in this volume develop these ideas. In terms of policy the papers suggest that economists should become a bit less certain in their policy conclusions, and that they expand their bag of tools supplementing their standard model with some additional models including agent based models, in which one does not use analytics to develop the pattern, but instead one uses computational power to deal with specification of models that are far beyond analytic solution; and non-linear dynamic stochastic models many of which are beyond analytic solution, but whose nature can be discovered by a combination of analytics and computer simulations. The volume is divided into four sections: general issues, modeling issues, applications, and policy issues. Each struggles with complicated ideas related to our general theme, and a number of