Using MAP-Elites to Optimize Self-Assembling Behaviors in a Swarm of Bio-micro-robots

We are interested in programming a swarm of molecular robots that can perform self-assembly to form specific shapes at a specific location. Programming such robot swarms is challenging for two reasons. First, the goal is to optimize both the parameters and the structure of chemical reaction networks...

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Bibliographic Details
Published in:bioRxiv
Main Authors: Cazenille, Leo, Bredeche, Nicolas, Aubert-Kato, Nathanael
Format: Paper
Language:English
Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 17.11.2019
Cold Spring Harbor Laboratory
Edition:1.1
Subjects:
Bioengineering
Robots
Self-assembly
evolutionary robotics
quality-diversity algorithms
Bio-micro-robots
swarm robotics
MAP-Elites
molecular programming
ISSN:2692-8205, 2692-8205
Online Access:Get full text
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Summary:We are interested in programming a swarm of molecular robots that can perform self-assembly to form specific shapes at a specific location. Programming such robot swarms is challenging for two reasons. First, the goal is to optimize both the parameters and the structure of chemical reaction networks. Second, the search space is both high-dimensional and deceptive. In this paper, we show that MAP-Elites, an algorithm that searches for both high-performing and diverse solutions, outperforms previous state-of-the-art optimization methods.
Bibliography:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
content type line 50
ISSN:2692-8205
2692-8205
DOI:10.1101/845594