mlsanityData to 7 Oct 2026

Safe Search for Stackelberg Equilibria in Extensive-Form Games

arXiv 2102.01775 ↗First posted 2 Feb 2021cs.GT cs.AIcited by 3

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Abstract (arXiv)

Stackelberg equilibrium is a solution concept in two-player games where the leader has commitment rights over the follower. In recent years, it has become a cornerstone of many security applications, including airport patrolling and wildlife poaching prevention. Even though many of these settings are sequential in nature, existing techniques pre-compute the entire solution ahead of time. In this paper, we present a theoretically sound and empirically effective way to apply search, which leverages extra online computation to improve a solution, to the computation of Stackelberg equilibria in general-sum games. Instead of the leader attempting to solve the full game upfront, an approximate "blueprint" solution is first computed offline and is then improved online for the particular subgames encountered in actual play. We prove that our search technique is guaranteed to perform no worse than the pre-computed blueprint strategy, and empirically demonstrate that it enables approximately solving significantly larger games compared to purely offline methods. We also show that our search operation may be cast as a smaller Stackelberg problem, making our method complementary to existing algorithms based on strategy generation.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 4 of its 26 references that are in the map. First posted on arXiv 2 Feb 2021.

Builds on

4 of 26 references.

References · 4

  1. 2017DeepStack: Expert-Level Artificial Intelligence in No-Limit Pokercited by 228
  2. 2017Safe and Nested Subgame Solving for Imperfect-Information Gamescited by 39
  3. 2013Solving Imperfect Information Games Using Decompositioncited by 27
  4. 2018Solving Large Sequential Games with the Excessive Gap Techniquecited by 16

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Citing papers per year: 2021: 1; 2022: 1; 2023: 1.

3 papers.