Collaborative Research: Quantum Decision Theory

合作研究:量子决策理论

基本信息

项目摘要

Research on human judgment and decision making has revealed a number of paradoxical findings that have resisted explanation under a common theoretical framework. These include violations of the sure thing axiom of decision making, interactions between inferences and decisions, violations of the reduction axiom of decision making, violations of the conjunctive and disjunctive axioms of probability theory, and order effects on judgments. In the past, separate and disconnected explanations have been proposed using variants of classic decision theory. This research proposes a unifying explanation for all of these paradoxical results based on a new quantum decision theory. Classic decision theory is based on classic probability theory. Probabilities are assigned to events defined as subsets of a universal set, which obey all the laws of Boolean algebra. Quantum decision theory is based on quantum probability theory. Probabilities are assigned to events defined as subspaces of a Hilbert space, which obey all the laws of Boolean algebra except the distributive axiom. Following from the distributive axiom, classic probability theory adheres to one of its most important theorems, the law of total probability. Because quantum logic does not have to obey the distributive law, quantum probabilities do not have to obey the law of total probability. Instead, quantum probability theory must obey another law called the doubly stochastic law, which the classic probability model does not obey. Hence, the two probability theories are fundamentally different and the critical question is which set of rules provides a better description of human behavior. The immediate goal of this research is to rigorously compare decision models built upon classical probability theory with those built from quantum probability theory. To rigorously compare quantum versus classical probability models of decision making, a series of experiments will be conducted. The experiments focus on tests of the law of total probability and tests of the law of double stochasticity, where the two classes of models make major and qualitatively different predictions. The research will accomplish three objectives: (1) develop a new quantum theory of human inference and decision making, (2) conduct new empirical tests of the fundamental laws of total probability and double stochasticity using human inference and decision behavior, and (3) rigorously compare and contrast classic versus quantum models of decision making with respect to the new empirical findings. A quantum or classic model will be preferred only if it provides a superior scientific explanation of the phenomena with respect to both accuracy and parsimony.The broad and long-term goal of this research program is to break new ground and pioneer a new path by building probabilistic and dynamic systems for social and behavioral sciences from quantum rather than classical probability principles. Previously, theorists in these fields have relied on mathematical models (e.g. stochastic differential equations) based on fundamental assumptions borrowed from classical physics. What are these fundamental assumptions? Are they overly restrictive? Social and behavioral scientists also face findings that remain paradoxical from a classic probability point of view. These paradoxes suggest that measurements in these fields may not always obey the law of total probability and entail different assumptions. This program of research also will contribute to the training of students at the undergraduate, graduate, and post doctoral levels at two major state universities. In addition to student training, the investigators will make an effort to train scientists in the area quantum cognition. They have conducted a full day tutorial at the annual Cognitive Science meeting and they plan to continue these tutorials in the future. They also plan to organize a special issue on Quantum Cognition in the Journal of Mathematical Psychology. New graduate courses on quantum cognition and decision making will be prepared and presented at the graduate level, and finally, a resource web site will be developed with tutorial and reference information on quantum theory for social and behavioral sciences.
对人类判断和决策的研究揭示了许多矛盾的发现,这些发现在一个共同的理论框架下无法解释。这些包括违反决策的确定性公理,推理和决策之间的相互作用,违反决策的还原公理,违反概率论的合取和析取公理,以及判断的顺序效应。在过去,已经提出了使用经典决策理论的变体的单独和断开的解释。这项研究提出了一个统一的解释所有这些矛盾的结果的基础上一个新的量子决策理论。经典决策理论是以经典概率论为基础的。 概率被分配给定义为全集子集的事件,这些子集遵守布尔代数的所有定律。量子决策理论是以量子概率论为基础的。概率被分配给定义为希尔伯特空间的子空间的事件,这些子空间遵守布尔代数的所有定律,除了分配公理。从分配公理出发,经典概率论坚持其最重要的定理之一,即全概率定律。因为量子逻辑不必服从分配律,量子概率也不必服从全概率律。相反,量子概率论必须遵守另一个被称为双随机定律的定律,经典概率模型不遵守这个定律。因此,这两种概率理论是根本不同的,关键问题是哪一套规则能更好地描述人类行为。这项研究的直接目标是严格比较基于经典概率论和量子概率论的决策模型。为了严格比较量子与经典决策概率模型,将进行一系列实验。实验侧重于测试的法律的总概率和测试的法律的双随机性,其中两类模型作出重大和定性不同的预测。该研究将完成三个目标:(1)开发一个新的人类推理和决策的量子理论,(2)使用人类推理和决策行为对全概率和双随机性的基本定律进行新的实证检验,(3)严格比较和对比经典与量子决策模型的新实证发现。一个量子或经典的模型将是首选,只有当它提供了一个上级的科学解释的现象方面的准确性和简约性。这个研究计划的广泛和长期的目标是开辟新天地,开拓一条新的道路,通过建立概率和动态系统的社会和行为科学从量子而不是经典的概率原则。以前,这些领域的理论家依赖于基于经典物理学基本假设的数学模型(例如随机微分方程)。这些基本假设是什么?它们是否过于严格?社会和行为科学家也面临着从经典概率观点来看仍然自相矛盾的发现。这些悖论表明,在这些领域的测量可能并不总是服从总概率定律,并需要不同的假设。这项研究计划也将有助于在两所主要州立大学的本科生,研究生和博士后水平的学生的培训。除了对学生进行培训外,研究人员还将努力培训量子认知领域的科学家。他们在年度认知科学会议上进行了一整天的教程,他们计划在未来继续这些教程。他们还计划在《数学心理学杂志》上组织一期关于量子认知的特刊。新的研究生课程量子认知和决策将准备和介绍在研究生水平,最后,资源网站将开发与教程和参考信息量子理论的社会和行为科学。

项目成果

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会议论文数量(0)
专利数量(0)

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Zheng Wang其他文献

Online electro-Fenton-mass spectrometry reveals 2,4 ',5-trichlorobiphenyl oxidation products and binding to organic matter
  • DOI:
  • 发表时间:
    2014
  • 期刊:
  • 影响因子:
    15.7
  • 作者:
    Stephan Kueppers;Zheng Wang;Xinyi Xiang;Shiwei Cao
  • 通讯作者:
    Shiwei Cao
Sequence characterization of microvariant alleles at DYS627 and DYS458
DYS627 和 DYS458 微变异等位基因的序列特征
Study on vibration performance and comfort of glulam beam and deck floor
胶合木梁及楼承板振动性能及舒适性研究
Ligand metathesis: a rational strategy for the synthesis of cubane-type heteroleptic iron-sulfur clusters relevant to the FeMo cofactor
配体复分解:合成与 FeMo 辅因子相关的立方烷型杂配铁硫簇的合理策略
  • DOI:
    10.1073/pnas.1801025115
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Gan Xu;Zheng Wang;Rong Ling;Jie Zhou;Xu-Dong Chen;Richard H. Holm
  • 通讯作者:
    Richard H. Holm
A compact lumped‐element two‐way differential to single‐ended Wilkinson power combiner with embedded impedance transformation
具有嵌入式阻抗变换的紧凑型集总元件双向差分到单端威尔金森功率组合器

Zheng Wang的其他文献

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{{ truncateString('Zheng Wang', 18)}}的其他基金

Examining the long-term social legacy of mega urban projects - A comparison of Shanghai and Dujiangyan City
审视巨型城市项目的长期社会遗产——上海与都江堰市的比较
  • 批准号:
    ES/W003104/2
  • 财政年份:
    2023
  • 资助金额:
    $ 23.84万
  • 项目类别:
    Research Grant
M4Secure: Making Memory Management More Secure
M4Secure:让内存管理更安全
  • 批准号:
    EP/X037304/1
  • 财政年份:
    2023
  • 资助金额:
    $ 23.84万
  • 项目类别:
    Research Grant
Modernise Compiler Technology With Deep Learning
通过深度学习实现编译器技术现代化
  • 批准号:
    EP/X018202/1
  • 财政年份:
    2023
  • 资助金额:
    $ 23.84万
  • 项目类别:
    Research Grant
Examining the long-term social legacy of mega urban projects - A comparison of Shanghai and Dujiangyan City
审视巨型城市项目的长期社会遗产——上海与都江堰市的比较
  • 批准号:
    ES/W003104/1
  • 财政年份:
    2022
  • 资助金额:
    $ 23.84万
  • 项目类别:
    Research Grant
Collaborate Research: Construct a General Hilbert Space Multi-dimensional Model
合作研究:构建通用希尔伯特空间多维模型
  • 批准号:
    1560501
  • 财政年份:
    2016
  • 资助金额:
    $ 23.84万
  • 项目类别:
    Standard Grant
SANDeRS: Smart, Adaptive Compilation for Dark Silicon
SANDERS:针对黑硅的智能、自适应编译
  • 批准号:
    EP/M01567X/1
  • 财政年份:
    2015
  • 资助金额:
    $ 23.84万
  • 项目类别:
    Research Grant
Distributed Heterogeneous Vertically IntegrateD ENergy Efficient Data centres
分布式异构垂直集成节能数据中心
  • 批准号:
    EP/M015793/1
  • 财政年份:
    2014
  • 资助金额:
    $ 23.84万
  • 项目类别:
    Research Grant
Collaborative Research: Quantum Decision Theory
合作研究:量子决策理论
  • 批准号:
    1153846
  • 财政年份:
    2012
  • 资助金额:
    $ 23.84万
  • 项目类别:
    Standard Grant

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    2344658
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