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Optimizing the Viability of Interacting Systems with Evolutionary Algorithms

  • 2026
  • OriginalPaper
  • Chapter
Published in:
Authors
Alice de Lapparent
Alberto Tonda
Rodolphe Sabatier
Evelyne Lutton
Isabelle Alvarez
Sophie Martin
Published in
Artificial Evolution
Publisher
Springer Nature Switzerland

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Abstract

This chapter explores the application of evolutionary algorithms (EA) to compute viability kernels for high-dimensional systems, focusing on multi-agent scenarios. It introduces viability theory as a framework for environmental and sustainability modeling, emphasizing the importance of viable strategies over single optimal solutions. The text addresses the challenges of interacting systems and presents a real-world agritourism project as a case study. Key topics include the use of EA to optimize agent commitments, the design of surrogate functions to accelerate optimization, and the analysis of the optimal solution. The chapter concludes with a discussion on the effectiveness of the proposed framework and its potential applications in various multi-agent systems.
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previous chapter Can Mutations Replace Local Search? Studying the Effect of Repeated Genetic Programming Operators in the Unrelated Machines Environment
next chapter Single-Objective Constrained Optimization for Gene Regulatory Networks Modeling
Title
Optimizing the Viability of Interacting Systems with Evolutionary Algorithms
Authors
Alice de Lapparent
Alberto Tonda
Rodolphe Sabatier
Evelyne Lutton
Isabelle Alvarez
Sophie Martin
Copyright Year
2026
Book
Artificial Evolution

Print ISBN: 978-3-032-07997-8

Electronic ISBN: 978-3-032-07998-5

Copyright Year: 2026

DOI
https://doi.org/10.1007/978-3-032-07998-5_12
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