activity
20172026
most citedDeep Learning for Procedural Content Generation

143 citations · 546 across the 35 of their papers we have counts for

collaborators

48 papers

cs.NE2026

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…

cs.AI2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.AI2025

PuzzleJAX: A Benchmark for Reasoning and Learning

Sam Earle, Graham Todd, Yuchen Li +5

We introduce PuzzleJAX, a GPU-accelerated puzzle game engine and description language designed to support rapid benchmarking of tree search, reinforcement learning, and LLM reasoni…