- author = "Steven Jorgensen and Ambroise Borbely and Erik Hemberg and Joseph Bates and Una-May O'Reilly",
- title = "Spatial Genetic Programming with the {S1} Processing Board",
- booktitle = "Genetic Programming Theory and Practice XXII",
- year = "2025",
- editor = "Bogdan Burlacu and Fabricio {Olivetti de Franca} and Alexander Lalejini and Stephen Kelly and Wolfgang Banzhaf",
- series = "Genetic and Evolutionary Computation",
- pages = "329--351",
- address = "Michigan State University, USA",
- month = jun # " 5-7",
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming, Linear Genetic Programming, EHW",
- isbn13 = "978-981-95-6397-5",
-
DOI = "
10.1007/978-981-95-6398-2_16",
- abstract = "...require specialized algorithmic adaptations but enable the evolution of exceptionally large, spatially structured populations. We describe the design and deployment of an evolutionary algorithm on the S1, starting with a spatially distributed genetic algorithm applied to the MaxOnes problem, and extending to two more sophisticated genetic programming representations: Linear Genetic Programming(LGP) and Cartesian Genetic Programming(CGP). Each approach is carefully adapted to exploit the S1 architectural strengths, including synchronous population updates and local neighborhood selection through hardware-supported communication. Additionally, we present a modular software library that abstracts away the S1 low-level features, simplifying the development of evolutionary algorithms on this platform. Our results confirm the S1 capability to efficiently evolve large populations, highlighting its potential for advancing research in large-scale, spatially structured genetic programming.",
-
notes = "lightning talk.
published in 2026 after the workshop",
