核心概念
The authors analyze the computational complexity of finding optimal commitments for various types of games, including Stackelberg and Bayesian games, with a focus on strategies and outcome-conditional utility transfers.
摘要
The content delves into the computational complexity of computing optimal commitments in different game scenarios. It explores the implications of commitment to strategies and payments, highlighting the importance of incentive compatibility. The study extends to Bayesian games, showcasing challenges in leader-follower interactions with private information.
統計資料
We find a mix of polynomial time algorithms and NP-hardness results.
In two-player games, optimal pure commitments can be found efficiently with dynamic programming.
In three-player games where players commit in sequence, the pure commitment case can be solved efficiently with LP while the mixed commitment case is NP-hard.
Optimal mixed commitments in two-player games can be computed in polynomial time.
Computing the leader’s optimal commitment is NP-hard even for three players and for games where the leader has only a single action.