Intelligent matter consisting of active particles

TL;DR

This chapter explores how active particle systems can emulate collective behaviors leading to intelligent matter, focusing on emergent computing and reservoir computing approaches for task-solving.

Contribution

It introduces a formal concept of intelligent matter and compares emergent computing with physical reservoir computing in active particle systems.

Findings

Active matter can be designed for specific computational tasks.

Reservoir computing schemes are feasible with ultrasonic or light-driven particles.

Emergent behaviors in active matter can lead to intelligent system functionalities.

Abstract

In this book chapter, we review how systems of simple motile agents can be used as a pathway to intelligent systems. It is a well known result from nature that large groups of entities following simple rules, such as swarms of animals, can give rise to much more complex collective behavior in a display of emergence. This begs the question whether we can emulate this behavior in synthetic matter and drive it to a point where the collective behavior reaches the complexity level of intelligent systems. Here, we will use a formalized notion of "intelligent matter" and compare it to recent results in the field of active matter. First, we will explore the approach of emergent computing in which specialized active matter systems are designed to directly solve a given task through emergent behavior. This we will then contrast with the approach of physical reservoir computing powered by the dynamics of active particle systems. In this context, we will also describe a novel reservoir computing scheme for active particles driven ultrasonically or via light refraction.