This chapter discusses the nature and the importance of spatial interactions in evolutionary computation. The current state of evolution theories is discussed. An interaction model is investigated which we have called Darwin’s
conjecture. Darwin argued that such a cycle is the most efficient for successful evolution. This bold conjecture has not yet been noticed in science. We confirm Darwin’s conjecture using an evolutionary game based on the iterated prisoner’s dilemma. A different interaction scheme, called the stepping-stone model is used by the Parallel Genetic Algorithm PGA. The PGA is used to solve combinatorial optimization problems. Then the Breeder Genetic Algorithm BGA used for global optimization of continuous functions is described. The BGA uses competition between subpopulations applying different strategies. This kind of interaction is found in ecological systems.