- author = "Camilo {De La Torre} and Sylvain Cussat-Blanc and Dennis Wilson and Yuri Lavinas",
- title = "On Search Trajectory Networks for Graph Genetic Programming",
- booktitle = "2nd GECCO workshop on Graph-based Genetic Programming",
- year = "2024",
- editor = "Dennis G. Wilson and Roman Kalkreuth and Eric Medvet and Giorgia Nadizar and Giovanni Squillero and Alberto Tonda and Yuri Lavinas",
- pages = "1681--1685",
- address = "Melbourne",
- series = "GECCO '24",
- month = "14 " # jul,
- organisation = "SIGEVO",
- publisher = "Association for Computing Machinery",
- publisher_address = "New York, NY, USA",
- keywords = "genetic algorithms, genetic programming, cartesian genetic programming, evolutionary computation, symbolic regression",
- isbn13 = "979-8-4007-0495-6",
-
DOI = "
doi:10.1145/3638530.3664169",
- size = "5 pages",
- abstract = "Cartesian Genetic Programming (CGP) allows for the optimization of interpretable function representations. However, comprehending the vast and combinatorially complex search space inherent to CGP remains challenging, particularly because multiple genotypes may correspond to identical functions. This paper studies the application of Search Trajectory Networks (STNs) to understand the search dynamics of CGP, specifically for symbolic regression tasks. Using STNs, we analyze the behavior of evolutionary search processes and uncover distinct phenomena, such as the presence of {"}portal{"} minima---critical junctures that facilitate sudden, beneficial shifts in the search trajectory, akin to findings in linear genetic programming. Our findings illustrate that while genetic interpretations are complex and often ambiguous, a functional analysis using STNs offers clear and actionable insights into the CGP search.",
-
notes = "Also known as
\cite{de-la-torre:2024:GECCOcomp2}
GECCO-2024 A Recombination of the 33rd International Conference on Genetic Algorithms (ICGA) and the 29th Annual Genetic Programming Conference (GP)",
