In evolutionary search, a weak child can be a valuable ancestor that makes high-fitness regions reachable. Immediate-return control is blind to this delayed utility, penalizing mutations through their immediate offspring even when they open productive future lineages. We formalize this hidden dynamic as the time value...
Matthew Siper, A. Khalifa, Julian Togelius· 0 citations
This work introduces an Evolutionary Language Model that searches over natural-language policy descriptions and compiles typed programs for execution and shows that language can serve as a steerable, execution-grounded search representation over executable program space.
Matthew Siper, A. Khalifa, Julian Togelius· 0 citations
Large language models can generate executable programs, which makes it possible to search directly over procedural content generators rather than individual levels. We study this approach in Sokoban, Zelda, Dangerous Dave, and Lode Runner. Each run evolves complete Python generators through language-model mutation and...
Matthew Siper, A. Khalifa, Julian Togelius· 0 citations
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