3 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.AI2025
A* Search Without Expansions: Learning Heuristic Functions with Deep Q-Networks
Forest Agostinelli, Shahaf S. Shperberg, Alexander Shmakov +3
Efficiently solving problems with large action spaces using A* search remains a significant challenge. This is because, for each iteration of A* search, the number of nodes generat…
cs.LG2024
Realizable Continuous-Space Shields for Safe Reinforcement Learning
Kyungmin Kim, Davide Corsi, Andoni Rodriguez +5
While Deep Reinforcement Learning (DRL) has achieved remarkable success across various domains, it remains vulnerable to occasional catastrophic failures without additional safegua…