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20242026
most citedPCGRLLM: Large Language Model-Driven Reward Design for Procedural Content Generation Reinforcement Learning

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cs.CL2024

Large Language Models and Games: A Survey and Roadmap

Roberto Gallotta, Graham Todd, Marvin Zammit +4

Recent years have seen an explosive increase in research on large language models (LLMs), and accompanying public engagement on the topic. While starting as a niche area within nat…

cs.LG2024

PCGRL+: Scaling, Control and Generalization in Reinforcement Learning Level Generators

Sam Earle, Zehua Jiang, Julian Togelius

Procedural Content Generation via Reinforcement Learning (PCGRL) has been introduced as a means by which controllable designer agents can be trained based only on a set of computab…

cs.AI2024

Autoverse: An Evolvable Game Language for Learning Robust Embodied Agents

Sam Earle, Julian Togelius

We introduce Autoverse, an evolvable, domain-specific language for single-player 2D grid-based games, and demonstrate its use as a scalable training ground for Open-Ended Learning…

cs.AI2024

Making New Connections: LLMs as Puzzle Generators for The New York Times' Connections Word Game

Tim Merino, Sam Earle, Ryan Sudhakaran +2

The Connections puzzle is a word association game published daily by The New York Times (NYT). In this game, players are asked to find groups of four words that are connected by a…

cs.GR2024

DreamCraft: Text-Guided Generation of Functional 3D Environments in Minecraft

Sam Earle, Filippos Kokkinos, Yuhe Nie +2

Procedural Content Generation (PCG) algorithms enable the automatic generation of complex and diverse artifacts. However, they don't provide high-level control over the generated c…

cs.CL2024

Missed Connections: Lateral Thinking Puzzles for Large Language Models

Graham Todd, Tim Merino, Sam Earle +1

The Connections puzzle published each day by the New York Times tasks players with dividing a bank of sixteen words into four groups of four words that each relate to a common them…