2 citations · 2 across the 5 of their papers we have counts for
7 papers
Programmable Cellular Automata
Ahmed Khalifa, Muhammad Umair Nasir, Matthew Siper +2
Cellular automata is a local computation paradigm where complex behavior can arise from local interactions between simple functions. This paradigm has been used to explain many sys…
Procedural Content Metageneration via Program Search and Continual Abstraction Discovery
Matthew Siper, Ahmed Khalifa, Julian Togelius
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 a…
The Time Value of Evolution
Matthew Siper, Ahmed Khalifa, Julian Togelius
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 mut…
ELMER: Evolutionary Language Model that Explores and Refines
Matthew Siper, Ahmed Khalifa, Julian Togelius
Program evolution can measure whether a mutation helped, but it rarely controls how far the mutation moves in behavior space. Syntactic edit size is an unreliable proxy: a small co…
Continuous Program Search
Matthew Siper, Muhammad Umair Nasir, Ahmed Khalifa +3
Genetic Programming yields interpretable programs, but small syntactic mutations can induce large, unpredictable behavioral shifts, degrading locality and sample efficiency. We fra…
Controllable Path of Destruction
Matthew Siper, Sam Earle, Zehua Jiang +2
Path of Destruction (PoD) is a self-supervised method for learning iterative generators. The core idea is to produce a training set by destroying a set of artifacts, and for each d…
Path of Destruction: Learning an Iterative Level Generator Using a Small Dataset
Matthew Siper, Ahmed Khalifa, Julian Togelius
We propose a new procedural content generation method which learns iterative level generators from a dataset of existing levels. The Path of Destruction method, as we call it, view…