A hierarchical graph transformer with layer-by-layer feedback reinforcement learning beats rule-based, MILP, and GNN baselines in a two-stage dynamic Colonel Blotto resource allocation game on graphs.
Multi-attribute game theoretic model for resource allocation in military attack-defense application,
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HGFormer: A Hierarchical Graph Transformer Framework for Two-Stage Colonel Blotto Games via Reinforcement Learning
A hierarchical graph transformer with layer-by-layer feedback reinforcement learning beats rule-based, MILP, and GNN baselines in a two-stage dynamic Colonel Blotto resource allocation game on graphs.