Neuromorphic Evolutionary Computation
IEEE World Congress on Computational Intelligence (WCCI) 2026, Maastricht, Netherlands
Abstract
Neuromorphic computing brings spiking dynamics and event-driven efficiency into the realm of optimisation. Evolutionary algorithms, long valued for their versatility, can now be re-imagined on this substrate. We first present the theoretical principles behind neuromorphic-based metaheuristics, highlighting their motivations, classification, and trade-offs. We then detail two neuromorphic evolutionary computation approaches: one includes a practical architecture in which units implement mutation and variation via spikes, and the other leverages the Basal-Ganglia-Thalamic loop. Finally, we discuss practical applications using open-source packages, showing participants how to design, run, and interpret neuromorphic optimisation experiments. This tutorial aims to demonstrate how spiking computation can shape a new generation of evolutionary search and open the way to applications in robotics, IoT, and embedded intelligence.