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生物学中的非合作博弈论与人类的合作推理。

Non-cooperative game theory in biology and cooperative reasoning in humans.

作者信息

Kabalak Alihan, Smirnova Elena, Jost Jürgen

机构信息

Max Planck Institute for Mathematics in the Sciences, Inselstrasse 22, 04103, Leipzig, Germany.

出版信息

Theory Biosci. 2015 Jun;134(1-2):17-46. doi: 10.1007/s12064-015-0210-x. Epub 2015 Jun 3.

Abstract

The readiness for spontaneous cooperation together with the assumptions that others share this cooperativity has been identified as a fundamental feature that distinguishes humans from other animals, including the great apes. At the same time, cooperativity presents an evolutionary puzzle because non-cooperators do better in a group of cooperators. We develop here an analysis of the process leading to cooperation in terms of rationality concepts, game theory and epistemic logic. We are, however, not attempting to reconstruct the actual evolutionary process. We rather want to provide the logical structure underlying cooperation in order to understand why cooperation is possible and what kind of reasoning and beliefs would lead to cooperative decision-making. Game theory depends on an underlying common belief in non-cooperative rationality of the players, and cooperativity similarly can utilize a common belief in cooperative rationality as its basis. We suggest a weaker concept of rational decision-making in games that encompasses both types of decision-making. We build this up in stages, starting from simple optimization, then using anticipation of the reaction of others, to finally arrive at reflexive and cooperative reasoning. While each stage is more difficult than the preceding, importantly, we also identify a reduction of complexity achieved by the consistent application of higher stage reasoning.

摘要

自发合作的意愿以及认为他人也具有这种合作性的假设,已被视为将人类与包括大猩猩在内的其他动物区分开来的一个基本特征。与此同时,合作性也带来了一个进化难题,因为在一群合作者中,不合作者表现得更好。我们在此依据理性概念、博弈论和认知逻辑,对合作产生的过程展开分析。然而,我们并非试图重构实际的进化过程。我们更想提供合作背后的逻辑结构,以便理解合作为何可能,以及何种推理和信念会导致合作性决策。博弈论依赖于参与者对非合作理性的潜在共同信念,而合作性同样可以将对合作理性的共同信念作为其基础。我们提出一种在博弈中更弱的理性决策概念,它涵盖了这两种决策类型。我们分阶段构建这一概念,从简单的优化开始,接着运用对他人反应的预期,最终达到反思性和合作性推理。虽然每个阶段都比前一个更难,但重要的是,我们还发现通过持续应用更高阶段的推理可以降低复杂性。

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