Coevolutionary Computation for Widget Optimization

Ada Lovelace Alan Turing
Abstract

We present a coevolutionary approach to widget optimization [1] that scales across conditions.

1 Introduction

Widgets are important devices [2] in many fields.

2 Methods

We measured widgets under controlled conditions.

FIGURE_CAPTION_DROP

The equation MATH_SHOULD_DROP was used here.

2.1 Sample preparation

We prepared samples carefully.

3 Results

We found significantly more widgets.

References