Dynamic protocol stacks have been identified as a method of improving the performance of process communication by constructing the protocol that meets it requirements with a minimum overhead. However, the design of these stacks is a complex process for human designers who must identify the correct elements and ordering. Genetic programming is a machine learning technique method for generating computer programs automatically. It has been applied to many areas including electronic circuit design, image classification and machine code creation. However, it has never been utilised in the area of communication protocols. The main aim of the project is to identify if genetic programming techniques can be applied to protocol construction using the JavaGroups toolkit and generate protocols automatically. This report describes the theory and application of genetic programming principles and also the technology behind and creation of dynamic protocols. There is also a description of the design and implementation of a genetic program that will create JavaGroups protocols to meet a set of requirements. The results from the experimentation of the implemented system identify that GP can automatically generate the correct protocol stack for a required communication type (e.g. reliable point-to-point). The uses of this method to generate any stack depending on the user’s requirement or within a changing real-time network situation are identified as future areas of work.