What is Needed to Promote an Asynchronous Program Evolution in Genetic Programing?

This paper focuses on an asynchronous program evolution in evolutionary computation, which is hard to evolve individuals (i.e., programs) effectively unlike a synchronous program evolution that evolves individuals effectively by selecting good parents after evaluations of all individuals in each generation. To tackle this problem, we explore the mechanism that can promote an asynchronous program evolution by selecting a good individual without waiting for evaluations of all individuals. For this purpose, this paper investigates the effectiveness of the proposed mechanism in genetic programing (GP) domain by evaluating it in the two types of problems (i.e., the arithmetic and Boolean problems). Through the intensive experiments of the eight kinds of testbeds under the two types of problems, the following implications have been revealed: (1) the program asynchronously evolved with the proposed mechanism can be completed with the shorter execution steps than the program asynchronously evolved without the proposed mechanism; and (2) the program asynchronously evolved with the proposed mechanism can be completed with mostly the same or shorter execution steps than the program synchronously evolved by the conventional GP.