1 citations · 2 across the 5 of their papers we have counts for
6 papers
State Trace Rationale As Auxiliary Task in Reinforcement Learning
Muhammad U. Nasir, Alex Vogt, Steven D. James +1
We propose STRAT, an auxiliary task that trains deep reinforcement learning (RL) agents to predict a short textual trace of their own state. Inspired by human spatial navigation, t…
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…
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…
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…
GameTraversalBenchmark: Evaluating Planning Abilities Of Large Language Models Through Traversing 2D Game Maps
Muhammad Umair Nasir, Steven James, Julian Togelius
Large language models (LLMs) have recently demonstrated great success in generating and understanding natural language. While they have also shown potential beyond the domain of na…
Word2World: Generating Stories and Worlds through Large Language Models
Muhammad U. Nasir, Steven James, Julian Togelius
Large Language Models (LLMs) have proven their worth across a diverse spectrum of disciplines. LLMs have shown great potential in Procedural Content Generation (PCG) as well, but d…