2 papers
cs.LG2026
Data-Augmented Game Starts for Accelerating Self-Play Exploration in Imperfect Information Games
JB Lanier, Nathan Monette, Pierre Baldi +1
Finding approximate equilibria for large-scale imperfect-information competitive games such as StarCraft, Dota, and CounterStrike remains computationally infeasible due to sparse r…
cs.LG2025
An Optimisation Framework for Unsupervised Environment Design
Nathan Monette, Alistair Letcher, Michael Beukman +4
For reinforcement learning agents to be deployed in high-risk settings, they must achieve a high level of robustness to unfamiliar scenarios. One method for improving robustness is…