A computational model based on Random Boolean Networks

For decades, the size of silicon CMOS transistors has decreased steadily while their performance has improved. As the devices approach their physical limits, the need for alternative materials, structures and computation schemes becomes evident. This paper considers a computation scheme based on an abstract model of gene regulatory networks called random Boolean networks. Our interest in random Boolean networks is due to their attractive fault-tolerant features. The parameters of a network can be tuned so that it exhibits a robust behavior in which minimal changes in networkpsilas connections, values of state variables, or associated functions, typically cause no variation in the networkpsilas dynamics. A computation scheme based on random networks also seems to be appealing for emerging technologies in which it is difficult to control the growth direction or precise alignment, e.g. carbon nanotubes.