6 papers
GVGAI-LLM: Evaluating Large Language Model Agents with Infinite Games
Yuchen Li, Cong Lin, Muhammad Umair Nasir +3
We introduce GVGAI-LLM, a video game benchmark for evaluating the reasoning and problem-solving capabilities of large language models (LLMs). Built on the General Video Game AI fra…
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…
Mortar: Evolving Mechanics for Automatic Game Design
Muhammad U. Nasir, Yuchen Li, Steven James +1
We present Mortar, a system for autonomously evolving game mechanics for automatic game design. Game mechanics define the rules and interactions that govern gameplay, and designing…
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…
ScriptDoctor: Automatic Generation of PuzzleScript Games via Large Language Models and Tree Search
Sam Earle, Ahmed Khalifa, Muhammad Umair Nasir +4
There is much interest in using large pre-trained models in Automatic Game Design (AGD), whether via the generation of code, assets, or more abstract conceptualization of design id…
Word2Minecraft: Generating 3D Game Levels through Large Language Models
Shuo Huang, Muhammad Umair Nasir, Steven James +1
We present Word2Minecraft, a system that leverages large language models to generate playable game levels in Minecraft based on structured stories. The system transforms narrative…