Intelligent matter consisting of active particles

arXiv:2512.13912v13 citationsh-index: 4Machine Intelligence for Materials Science
Originality Synthesis-oriented
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This is an incremental review exploring pathways to intelligent matter for researchers in active matter and emergent computing.

The chapter reviews how systems of simple motile agents can emulate natural collective behaviors to potentially achieve intelligent systems, comparing emergent computing and physical reservoir computing approaches.

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.

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