Data Types as a More Ergonomic Frontend for Grammar-Guided Genetic Programming

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Proposes encoding grammars as an internal DSL in the host language (Python), uses the host type system for autocomplete, linting and type checks, and implements Meta-Handlers to override tree generation and express attribute-grammar semantics (e.g. age constrained 0–200, probabilistic primaries with 3× weight). Provides a working Python implementation and empirical comparison to PonyGE2 on 5 benchmarks showing comparable runtime and same expressive power as BNF/EBNF plus attribute grammars, with measurably better ergonomics for non‑CS users.

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" chapters (12)

1. 0:00Intro
2. 0:15GENETIC PROGRAMMING
3. 3:10DEFINING THE SEARCH SPACE LASIGE
4. 5:56CHALLENGES IN GRAMMAR-GUIDED GP LASIGE
5. 7:26MOTIVATION
6. 8:02DATATYPE ENCODING
7. 9:15REAL-WORLD EXAMPLE
8. 9:56METAHANDLERS
9. 10:44EXPRESSIVE POWER
10. 11:34PERFORMANCE
11. 12:09ERGONOMICS
12. 14:01BONUS CONCLUSIONS