少点错误 11月11日 07:42
开放策略独裁者游戏:揭示公开透明下的合作新模式
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受1980年迭代囚徒困境竞赛的启发,新的“开放策略独裁者游戏”将策略的透明度提升到新高度。参与者以自然语言描述其策略,并由大型语言模型模拟独裁者游戏,其中一方的决策会考虑到另一方的策略描述。该游戏奖励公平而非零和博弈,并探讨在策略完全可见的情况下,合作、公平或剥削是否会成为主导。这次实验将检验透明度是否能稳定合作,以及语言模型在模拟决策和理性均衡中的作用,为理解人工智能时代的合作模式提供新视角。

💡 开放策略独裁者游戏是对经典合作博弈的创新性拓展,将策略的可见性作为核心变量。与1980年罗伯特·阿克塞尔罗德的迭代囚徒困境竞赛不同,该游戏要求参与者以自然语言清晰阐述其行动原则,并让AI(Claude Sonnet 4.5)在模拟的“独裁者游戏”中,将这些策略描述纳入决策考量,从而探索在完全透明的环境下合作的可能性。

🤝 该游戏的核心机制在于“知己知彼”的决策过程。每一轮,独裁者在分配固定资源时,不仅知道自己的策略,还能直接阅读接收者的策略描述。这种完全的可见性,加上游戏奖励公平(收益的对数函数)而非零和博弈,迫使参与者重新审视合作与对抗的平衡,并可能催生出基于相互理解和预测的新型合作策略。

🧠 游戏结果对于理解人工智能(AI)和超人工智能(Superintelligence)的发展具有重要意义。它旨在探究在策略完全公开透明的情况下,是否会出现条件性合作、互惠公平,抑或是新的剥削模式。同时,它也试图检验语言模型作为裁判或参与者,能否模拟出功能决策理论(FDT)所设想的“反思均衡”,即在逻辑上一致的决策过程中达成合作。

💡 实验结果将揭示透明度对合作稳定性的影响:是会巩固合作,还是会暴露新的脆弱性?通过参与者提交的策略及其在多轮对抗中的表现,研究人员可以收集宝贵数据,为理解和设计未来AI系统中的合作机制提供理论支持和实践指导,尤其是在AI之间或AI与人类之间可能出现的“读心术”情境下。

Published on November 10, 2025 11:26 PM GMT

In 1980, Robert Axelrod invited researchers around the world to submit computer programs to play the Iterated Prisoner’s Dilemma.
The results — where Tit for Tat famously won — transformed how we think about cooperation.
What mattered most wasn’t intelligence or aggression, but a few simple principles: be nice, retaliate, forgive, and be clear.

That insight reshaped evolutionary game theory and inspired decades of work in economics and social science.

But Axelrod’s agents were opaque. They couldn’t read each other’s source code.

Enter the Open Strategy Dictator Game

The Open Strategy Dictator Game asks: What happens when strategies are fully visible?
Each participant submits a natural-language strategy description — a few paragraphs of text explaining how their agent behaves.
Every round, a large language model (Claude Sonnet 4.5) simulates a one-shot dictator game where one strategy divides a fixed endowment between itself and a recipient.
Crucially, the dictator’s decision prompt includes the text of the other player's strategy.

In other words: you decide how to act knowing exactly who you’re facing — and they know you know.

Utilities are logarithmic in the received share, so the game rewards fairness rather than zero-sum aggression.
And since the tournament is round-robin, each strategy will also appear as a recipient many times — facing both selfish exploiters and conditional cooperators.

 

Why it matters

This setting sits at the intersection of three interesting topics:

 

What we might learn

 

If Axelrod’s tournament showed how cooperation emerges in the dark,
the Open Strategy Dictator Game explores how it survives in the light.

You can join the experiment, submit your strategy, and help test whether open cooperation can still win when everyone can read your mind.

Github: https://github.com/michaelrglass/os-fdt

Simple Initial Tournament Results: https://michaelrglass.github.io/os-fdt/



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开放策略独裁者游戏 Open Strategy Dictator Game 合作博弈 人工智能 AI 透明度 功能决策理论 FDT 迭代囚徒困境 Iterated Prisoner's Dilemma 策略透明 游戏理论
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