🤖 AI Summary
This study addresses the open problem regarding the computational complexity of Nash equilibria in discrete multiplayer Blotto games with player-specific battlefield valuations. By leveraging computational complexity theory and PPAD reduction techniques, this work systematically analyzes the boundaries of equilibrium computation under varying resource constraints and tie-breaking rules. The primary contribution is the first proof establishing the PPAD-hardness of computing constant-factor approximate equilibria in the three-player setting, thereby revealing a fundamental complexity dichotomy between uniform and non-uniform tie-breaking rules. Furthermore, this research establishes the PPAD-completeness of the associated problems and delineates strict boundaries between polynomial-time solvable special cases and computationally hard instances.
📝 Abstract
We study equilibrium computation in discrete multiplayer Colonel Blotto games with player-specific battlefield values. In the two-player model with common battlefield values, equilibria can be computed in polynomial time. We show that this tractability breaks down in the multiplayer model with player-specific values under the standard uniform tie-breaking rule. In particular, computing a $(c/n)$-approximate Nash equilibrium is PPAD-hard for some constant $c>0$, even when every player has three resources, where $n$ is the number of players. The main technical step is PPAD-hardness for computing a constant-approximate well-supported Nash equilibrium. In contrast, under uniform tie-breaking, a pure Nash equilibrium can be computed in polynomial time when every player has one resource. We also prove PPAD membership for computing $\varepsilon$-approximate Nash equilibria for inverse-exponentially small $\varepsilon$. Finally, for non-uniform monotone tie-breaking, we show PPAD-hardness even when every player has one resource and all players have identical battlefield values.