Author: Alex Lalejini

Signal GP, an Introduction

Signal GP, an Introduction

Genetic programming (GP) is the application of natural principles to evolve computer programs rather than writing them by hand. Here, I introduce Signal GP, a new type of linear GP representation designed to more directly capture the event-driven programming paradigm, allowing evolved programs to handle signals from the environment or from other agents in a more biologically inspired way than traditional linear GP representations. GP is successful across a growing set of problem domains. Signal GP targets problems where programs, much like biological organisms, must react on-the-fly to signals in the environment or from other agents. I’ll address the following questions in this blog post: What is linear genetic programming? What exactly is the event-driven programming paradigm, why is it so powerful, and why do we want to capture it in GP? And, how exactly does […]