SignalGP-Lite: Event Driven Genetic Programming Library for Large-Scale Artificial Life Applications

TL;DR

SignalGP-Lite is a streamlined, event-driven genetic programming library that significantly accelerates large-scale artificial life simulations while maintaining solution quality comparable to existing methods.

Contribution

The paper introduces SignalGP-Lite, a new library that reduces control flow overhead, enabling faster large-scale artificial life experiments with comparable solution quality.

Findings

Achieved 8x to 30x speedup in benchmarks

Maintained solution quality on complex signal-response problems

Enabled larger-scale artificial life experiments

Abstract

Event-driven genetic programming representations have been shown to outperform traditional imperative representations on interaction-intensive problems. The event-driven approach organizes genome content into modules that are triggered in response to environmental signals, simplifying simulation design and implementation. Existing work developing event-driven genetic programming methodology has largely used the SignalGP library, which caters to traditional program synthesis applications. The SignalGP-Lite library enables larger-scale artificial life experiments with streamlined agents by reducing control flow overhead and trading run-time flexibility for better performance due to compile-time configuration. Here, we report benchmarking experiments that show an 8x to 30x speedup. We also report solution quality equivalent to SignalGP on two benchmark problems originally developed to test the ability of evolved programs to respond to a large number of signals and to modulate signal response based on context.