Evolving Graphs with Semantic Neutral Drift
| Autor: | Detlef Plump, Timothy Atkinson, Susan Stepney |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Theoretical computer science Computer science Computer Science - Neural and Evolutionary Computing Genetic programming 0102 computer and information sciences 02 engineering and technology 01 natural sciences Graph Computer Science Applications 010201 computation theory & mathematics 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Neural and Evolutionary Computing (cs.NE) Equivalence (formal languages) |
| ISSN: | 1567-7818 |
| Popis: | We introduce the concept of Semantic Neutral Drift (SND) for genetic programming (GP), where we exploit equivalence laws to design semantics preserving mutations guaranteed to preserve individuals’ fitness scores. A number of digital circuit benchmark problems have been implemented with rule-based graph programs and empirically evaluated, demonstrating quantitative improvements in evolutionary performance. Analysis reveals that the benefits of the designed SND reside in more complex processes than simple growth of individuals, and that there are circumstances where it is beneficial to choose otherwise detrimental parameters for a GP system if that facilitates the inclusion of SND. |
| Databáze: | OpenAIRE |
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