Creative AI Through Evolutionary Computation: Principles and Examples

TL;DR

This paper discusses how evolutionary computation can be used to generate creative solutions in complex search spaces, positioning it as a promising approach for advancing artificial intelligence beyond traditional methods.

Contribution

It highlights principles and examples of using evolutionary computation for creative AI, emphasizing its potential as the next major paradigm after deep learning.

Findings

Evolutionary computation effectively finds creative solutions in high-dimensional spaces.

Population-based search techniques are suitable for real-world problem solving.

Creative AI via evolutionary methods is a promising future direction.

Abstract

The main power of artificial intelligence is not in modeling what we already know, but in creating solutions that are new. Such solutions exist in extremely large, high-dimensional, and complex search spaces. Population-based search techniques, i.e. variants of evolutionary computation, are well suited to finding them. These techniques make it possible to find creative solutions to practical problems in the real world, making creative AI through evolutionary computation the likely "next deep learning."