The synthesis of stochastic processes using genetic programming is investigated. Stochastic process behaviours take the form of time series data, in which quantities of interest v...
Recent experimental advances facilitate the collection of time series data that indicate which genes in a cell are expressed. This paper proposes an efficient method to generate th...
Nathan A. Barker, Chris J. Myers, Hiroyuki Kuwahar...
—We present a new distributed genetic algorithm that can be used to extract useful information from distributed, large data over the network. The main idea of the proposed algori...
Hyunjung Lee, Byonghwa Oh, Jihoon Yang, Seonho Kim
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
This paper presents an extension to genetic programming to allow the evolution of programs containing local variables with static scope which obey the invariant that all variables...