Department of Computer Science, University of Bristol, UK.
Anim Cogn. 2011 Jul;14(4):465-76. doi: 10.1007/s10071-011-0387-4. Epub 2011 Mar 1.
Animals (including humans) often face circumstances in which the best choice of action is not certain. Environmental cues may be ambiguous, and choices may be risky. This paper reviews the theoretical side of decision-making under uncertainty, particularly with regard to unknown risk (ambiguity). We use simple models to show that, irrespective of pay-offs, whether it is optimal to bias probability estimates depends upon how those estimates have been generated. In particular, if estimates have been calculated in a Bayesian framework with a sensible prior, it is best to use unbiased estimates. We review the extent of evidence for and against viewing animals (including humans) as Bayesian decision-makers. We pay particular attention to the Ellsberg Paradox, a classic result from experimental economics, in which human subjects appear to deviate from optimal decision-making by demonstrating an apparent aversion to ambiguity in a choice between two options with equal expected rewards. The paradox initially seems to be an example where decision-making estimates are biased relative to the Bayesian optimum. We discuss the extent to which the Bayesian paradigm might be applied to the evolution of decision-makers and how the Ellsberg Paradox may, with a deeper understanding, be resolved.
动物（包括人类）经常面临这样的情况：最佳行动选择并不确定。环境线索可能模棱两可，选择可能存在风险。本文回顾了不确定性下决策的理论方面，特别是针对未知风险（模糊性）。我们使用简单的模型表明，无论收益如何，是否最优地偏向概率估计取决于这些估计是如何生成的。特别是，如果估计是在具有合理先验的贝叶斯框架中计算的，那么最好使用无偏估计。我们回顾了动物（包括人类）被视为贝叶斯决策者的证据的程度。我们特别关注 Ellsberg 悖论，这是实验经济学中的一个经典结果，其中人类受试者在两个具有相同预期收益的选项之间的选择中表现出对模糊性的明显厌恶，似乎偏离了最优决策。这个悖论最初似乎是一个决策估计相对于贝叶斯最优存在偏差的例子。我们讨论了贝叶斯范式在决策者进化中的应用程度，以及 Ellsberg 悖论在更深入的理解下如何得到解决。
