Reinforcement Strategies in General Lotto Games

• 成果类型: Article
• 署名作者: Paarporn, Keith; Chandan, Rahul; Alizadeh, Mahnoosh; Marden, Jason R.
• 署名单位: University of Colorado System; University of Colorado at Colorado Springs; University of California System; University of California Santa Barbara
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3471411
• 发表日期: 2025
• 关键词: colonel-blotto; contests

摘要

Strategic decisions are often made over multiple periods of time, wherein decisions made earlier impact a competitor's success in later stages. In this article, we study these dynamics in General Lotto games, a class of models describing the competitive allocation of resources between two opposing players. We propose a two-stage formulation where one of the players has reserved resources that can be strategically preallocated across the battlefields in the first stage of the game as reinforcements. The players then simultaneously allocate their remaining real-time resources, which can be randomized, in a decisive final stage. Our main contributions provide complete characterizations of the optimal reinforcement strategies and resulting equilibrium payoffs in these multistage General Lotto games. Interestingly, we determine that real-time resources are at least twice as effective as reinforcement resources when considering equilibrium payoffs.