Heuristics and Biases are (Nearly) Optimal: A Fresh Programmatic Study of Heuristics and Biases in Human Decision-Making

我们的决定塑造了我们的生活：选择什么样的职业道路;如何投资;选择伴侣;如何获得幸福。我们的应用程序提出了计算机模拟，数学建模和心理学实验，以理解和解释人类决策中的核心问题。我们的研究计划的广泛目标是提供一种新的方式来理解人类决策中的逻辑和偏见，通过系统地为它们开发一个合理的基础。我们的研究计划挑战了人们普遍认为人类认知是系统性错误的观点，通过证明决策在给定的环境条件和认知限制下几乎是最佳的，从而提供了一种新的积极的认知观点。流行的观点是，判断和决策充满了认知偏见和偏离理性，因为人们使用快速但不准确（次优）的推理。我们将建立数学上严格的最优性保证，强烈挑战这一主导观点，从而提供了一个完全不同的角度对生态学。我们的新框架补充合理性研究，发展成为一个更丰富的研究计划，试图表明，在给定的环境条件和认知局限性，行为学几乎是最佳的。为这一行的工作提供支持证据，我们的初步工作表明，我们的框架产生强大的最佳保证一个著名的启发式，采取最好的。此外，与诺贝尔奖得主前景理论和其他当前的方法相比，我们提出了一个新的启发式决策模型，称为SbEU（基于样本的预期效用）。有效地结合了两个非常成功的认知理论，预期效用理论和有界最优性，SbEU独特地模拟，从而解释了人类决策中的广泛的主要发现。值得注意的是，SbEU是第一个，也是迄今为止唯一一个在风险、基于价值和博弈论决策之间架起桥梁的有界最优启发式模型。我们的研究计划提供了一个新的，统一的，精确的，正式的解释，对人类决策的几个庞大的文献。我们的初步模型将被细化，扩展，并应用于更多的实证研究结果。我们的模型的新预测将在新的心理学实验中进行实证检验。我们的假设是，人类以一种有限最优的方式做出决策：做出理性的决策，受环境条件以及他们面临的计算和认知限制的影响。我们希望这项工作能引发认知科学的重大范式转变，从一个看似无穷无尽的无法解释的偏见列表到一个统一的有限理性理论。这将从根本上改变我们目前理解人类认知的方式，对决策科学、政策制定和日常生活决策产生深远影响。因此，我们的研究对科学家和外行都非常重要。

Our decisions shape our lives: what career path to choose; how to invest; choice of partner; how to achieve happiness. Our application proposes computer simulations, math modeling, and psychology experiments to understand and explain central issues in human decision-making. The broad goal of our research program is to provide a new way of understanding heuristics and biases in human decision-making, by systematically developing a rational basis for them. Our research program challenges the widely held view that human cognition is systematically erroneous, offering instead a new and positive view of cognition by demonstrating that decision-making is nearly optimal given environmental conditions and cognitive limitations. The prevailing view is that judgment and decision-making are filled with cognitive biases and deviations from rationality, because people use fast but inaccurate (sub-optimal) heuristics. We will establish mathematically rigorous optimality guarantees for heuristics that strongly challenge this dominant view, thus offering a radically different perspective on heuristics. Our new framework complements rationality research, developing it into a richer research program by attempting to show that heuristics are nearly optimal given environmental conditions and cognitive limitations. Providing supporting evidence for this line of work, our preliminary work shows that our framework yields strong optimally guarantees for a well-known heuristic, Take-the-Best. Also, in contrast to Nobel-winning Prospect Theory and other current approaches, we present a new heuristic model of decision-making, called SbEU (Sample-based Expected Utility). Effectively combining two highly successful theories of cognition, expected utility theory and bounded optimality, SbEU uniquely simulates and thus explains a wide range of major findings in human decision-making. Notably, SbEU is the first, and so far the only, boundedly-optimal heuristic model that bridges between risky, value-based, and game-theoretic decision-making. Our research program provides a novel, unified, precise, formal explanation of several vast literatures on human decision-making. Our preliminary models will be refined, extended, and applied to more empirical findings. Novel predictions of our models will be empirically tested in new psychology experiments. Our hypothesis is that humans make decisions in a boundedly-optimal fashion: making rational decisions, subject to environmental conditions and the computational and cognitive limitations they are faced with. We expect this work to provoke a major paradigm shift in cognitive science, from a seemingly endless list of unexplained biases to a unified theory of bounded rationality. This would fundamentally change the way we currently understand human cognition, with far-reaching implications for decision sciences, policymaking, and daily-life decisions. As such, our research is of great importance for scientists and laypeople alike.