Broekaert Jan, Basieva Irina, Blasiak Pawel, Pothos Emmanuel M
Department of Psychology, City, University of London, London EC1V OHB, UK
Department of Psychology, City, University of London, London EC1V OHB, UK.
Philos Trans A Math Phys Eng Sci. 2017 Nov 13;375(2106). doi: 10.1098/rsta.2016.0387.
Quantum probability theory (QPT) has provided a novel, rich mathematical framework for cognitive modelling, especially for situations which appear paradoxical from classical perspectives. This work concerns the dynamical aspects of QPT, as relevant to cognitive modelling. We aspire to shed light on how the mind's driving potentials (encoded in Hamiltonian and Lindbladian operators) impact the evolution of a mental state. Some existing QPT cognitive models do employ dynamical aspects when considering how a mental state changes with time, but it is often the case that several simplifying assumptions are introduced. What kind of modelling flexibility does QPT dynamics offer without any simplifying assumptions and is it likely that such flexibility will be relevant in cognitive modelling? We consider a series of nested QPT dynamical models, constructed with a view to accommodate results from a simple, hypothetical experimental paradigm on decision-making. We consider Hamiltonians more complex than the ones which have traditionally been employed with a view to explore the putative explanatory value of this additional complexity. We then proceed to compare simple models with extensions regarding both the initial state (e.g. a mixed state with a specific orthogonal decomposition; a general mixed state) and the dynamics (by introducing Hamiltonians which destroy the separability of the initial structure and by considering an open-system extension). We illustrate the relations between these models mathematically and numerically.This article is part of the themed issue 'Second quantum revolution: foundational questions'.
量子概率理论(QPT)为认知建模提供了一个新颖、丰富的数学框架,特别是对于那些从经典视角看来似乎自相矛盾的情况。这项工作关注与认知建模相关的QPT的动力学方面。我们希望阐明思维的驱动潜能(编码在哈密顿算符和林德布拉德算符中)如何影响心理状态的演化。一些现有的QPT认知模型在考虑心理状态如何随时间变化时确实采用了动力学方面,但通常会引入一些简化假设。在没有任何简化假设的情况下,QPT动力学提供了何种建模灵活性,以及这种灵活性在认知建模中是否可能具有相关性?我们考虑了一系列嵌套的QPT动力学模型,其构建目的是适应一个关于决策的简单假设实验范式的结果。我们考虑比传统使用的哈密顿量更复杂的哈密顿量,以探索这种额外复杂性的假定解释价值。然后,我们继续比较简单模型与在初始状态(例如具有特定正交分解的混合态;一般混合态)和动力学方面(通过引入破坏初始结构可分离性的哈密顿量并考虑开放系统扩展)的扩展模型。我们用数学和数值方法说明了这些模型之间的关系。本文是主题为“第二次量子革命:基础问题”的特刊的一部分。