DQN and PPO policies, trained with a graph-aware action mask called an action-displacement adjacency matrix, beat random and greedy baselines on multi-step Colonel Blotto games on small graphs.
Planning for opportunistic surveil- lance with multiple robots,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Reinforcement Learning for Game-Theoretic Resource Allocation on Graphs
DQN and PPO policies, trained with a graph-aware action mask called an action-displacement adjacency matrix, beat random and greedy baselines on multi-step Colonel Blotto games on small graphs.