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

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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…