GENETIC PROGRAMMING WITH LINEAR REPRESENTATION -- A SURVEY <s> Cartesian Genetic Programming <s> Parallel Distributed Genetic Programming (PDGP) is a new form of Genetic Programming (GP) suitable for the development of programs with a high degree of parallelism. Programs are represented in PDGP as graphs with nodes representing functions and terminals, and links representing the flow of control and results. The paper presents the representations, the operators and the interpreters used in PDGP, and describes experiments in which PDGP has been compared to standard GP. <s> BIB001 </s> GENETIC PROGRAMMING WITH LINEAR REPRESENTATION -- A SURVEY <s> Cartesian Genetic Programming <s> Parallel Distributed Genetic Programming (PDGP) is a new form of genetic programming suitable for the development of parallel programs in which symbolic and neural processing elements can be combined in a free and natural way. This paper describes the representation for programs and the genetic operators on which PDGP is based. Experimental results on the XOR problem axe also reported. <s> BIB002 </s> GENETIC PROGRAMMING WITH LINEAR REPRESENTATION -- A SURVEY <s> Cartesian Genetic Programming <s> Cartesian Genetic Programming is a form of genetic programming. It is increasing in popularity. It was developed by Julian Miller with Peter Thomson in 1997. In its classic form it uses a very simple integer based genetic representation of a program in the form of a directed graph. In a number of studies, it has been shown to be efficient in comparison with other GP techniques. ::: Since then, the classical form of CGP has been enhanced in various ways by including automatically defined functions. ::: Most recently, it has been developed by Julian Miller. Wolfgang Banzhaf and Simon Harding to include self-modification operators. This again has increased its efficiency. ::: The tutorial will cover the basic technique, advanced developments and applications to a variety of problem domains. <s> BIB003
Cartesian Genetic Programming (CGP) 8 is a GP technique that encodes chromosomes in graph structures rather than trees like standard GP. The motivation for this representation is that the graphs are more general than the tree structures, thus allowing the construction of more complex computer programs BIB003 . Cartesian GP used a graph representation very similar to Poli's parallel distributed GP (PDGP)  BIB001 BIB002   .