本文以冯·诺伊曼为起点：他在 1940 年代中期相隔仅 1 年出版两项代表作——一本约 600 页、奠定博弈论基础的著作，以及一份影响深远、描述可执行不同程式之新型电脑的技术报告。

此后两个领域多半各自发展约 50 年；到 20 世纪末，研究者逐步看见互补性：网际网路等多行为者情境（如交通与通讯壅塞）迫使电脑科学面对策略互动，而计算与演算法工具也反过来帮助分析博弈。

关键进展集中在 1990 年代与 2000 年代初；2008 年研究指出某些博弈中找出纳许均衡在计算上极其困难，并延伸到玩家资讯不足时的收敛速度限制。近年价格设定演算法引发「演算法合谋」疑虑；2024 年又出现以新设计的自我对弈游戏，提升大型语言模型输出一致性与可靠性的方向，显示两者结合在约 30 年后仍持续演化。

The article links game theory and computer science through John von Neumann, who published two landmark works only one year apart in the mid-1940s: a roughly 600-page book founding modern game theory and a technical report that shaped programmable computer design.

Despite that proximity, the fields largely developed separately for about 50 years. Late in the 20th century, computer scientists facing many-actor settings (traffic and network congestion) drew on game-theoretic ideas, while computational methods began clarifying core questions about strategic games.

Work accelerated in the 1990s and early 2000s. A celebrated 2008 result showed that computing Nash equilibria can be extremely hard in some games, alongside limits on how fast players reach equilibrium under incomplete information. New pressures come from widespread pricing algorithms and fears of algorithmic collusion; in 2024, researchers also designed self-play games to make large language model outputs more consistent and reliable, indicating an evolving 30-year convergence.