How particular is the physics of the free energy principle?

How particular is the physics of the free energy principle?
复制标题

DOI:
10.1016/j.plrev.2021.11.001
复制
发表时间:
2022-03
影响因子:
11.7
通讯作者:
Buckley CL
Buckley CL
中科院分区:
生物学2区
文献类型:
--
作者:
Aguilera M;Millidge B;Tschantz A;Buckley CL

文献摘要

参考文献

被引文献

相似文献

自由能原理(FEP)指出,任何动力系统都可以被解释为对其周围环境进行贝叶斯推理。虽然在理论上,FEP适用于各种系统,但几乎没有在具体系统中直接探索或证明该原则。在这项工作中,我们深入研究了在最简单的可能系统集合(弱耦合非平衡线性随机系统)中推导FEP所需的假设。具体来说,我们探讨(一)如何一般的要求施加在一个系统的统计结构和(二)如何信息的FEP是关于这样的系统的行为。我们发现,两个要求的FEP -马尔可夫毯条件(即排除内部和外部状态之间的直接耦合的统计边界)和严格的限制,其螺线管流(即趋势驱动系统的平衡)-只适用于一个非常狭窄的参数空间。合适的系统需要不存在感知-动作不对称性,这对于与环境交互的生命系统来说是非常不寻常的。更重要的是,我们观察到,在数学上的核心步骤的论点,连接的行为系统变分推理,依赖于一个系统的平均状态的动态与这些状态的平均动态之间的隐含等价。即使对于线性随机系统,这种等价性一般也不成立,因为它需要从系统的相互作用历史中有效解耦。这些意见是至关重要的评估的一般性和适用性的FEP,并表明存在重大问题的理论在其目前的形式。这些问题使得FEP不能直接应用于这里研究的简单线性系统,并表明在该理论可以应用于描述生命和认知过程的复杂系统之前,还需要更多的发展。我们回顾了自由能原理(FEP)在一个家庭的分析易处理的非平衡线性系统。我们研究如何一般和如何信息的FEP是在这类系统。我们发现,FEP的关键假设限制了它的适用性,一个非常狭窄的空间所研究的线性系统。其次,核心步骤依赖于平均动态和动态平均之间的等价性。因此,FEP无法很好地描述系统的(依赖于历史的)行为。
The free energy principle (FEP) states that any dynamical system can be interpreted as performing Bayesian inference upon its surrounding environment. Although, in theory, the FEP applies to a wide variety of systems, there has been almost no direct exploration or demonstration of the principle in concrete systems. In this work, we examine in depth the assumptions required to derive the FEP in the simplest possible set of systems – weakly-coupled non-equilibrium linear stochastic systems. Specifically, we explore (i) how general the requirements imposed on the statistical structure of a system are and (ii) how informative the FEP is about the behaviour of such systems. We discover that two requirements of the FEP – the Markov blanket condition (i.e. a statistical boundary precluding direct coupling between internal and external states) and stringent restrictions on its solenoidal flows (i.e. tendencies driving a system out of equilibrium) – are only valid for a very narrow space of parameters. Suitable systems require an absence of perception-action asymmetries that is highly unusual for living systems interacting with an environment. More importantly, we observe that a mathematically central step in the argument, connecting the behaviour of a system to variational inference, relies on an implicit equivalence between the dynamics of the average states of a system with the average of the dynamics of those states. This equivalence does not hold in general even for linear stochastic systems, since it requires an effective decoupling from the system's history of interactions. These observations are critical for evaluating the generality and applicability of the FEP and indicate the existence of significant problems of the theory in its current form. These issues make the FEP, as it stands, not straightforwardly applicable to the simple linear systems studied here and suggest that more development is needed before the theory could be applied to the kind of complex systems that describe living and cognitive processes. We review the free energy principle (FEP) in a family of analytically tractable non-equilibrium linear systems. We study how general and how informative the FEP is in this class of systems. We find that crucial assumptions of the FEP restrict its applicability to a very narrow space of the studied linear systems. Secondly, a core step relies on an equivalence between the dynamics of the average and the average of the dynamics. As a result, the FEP does not result in a good description of the (history-dependent) behaviour of a system.
DOI: 10.1162/neco_a_00912
发表时间: 2017-01-01
期刊: NEURAL COMPUTATION
影响因子: 2.9
作者:
Friston, Karl;FitzGerald, Thomas;Pezzulo, Giovanni
通讯作者: Pezzulo, Giovanni
DOI: 10.1017/s0140525x21002351
发表时间: 2022-01-01
影响因子: 29.3
作者:
Bruineberg, Jelle;Dolega, Krzysztof;Baltieri, Manuel
通讯作者: Baltieri, Manuel
DOI: 10.1016/j.neuroimage.2006.08.035
发表时间: 2007-01-01
期刊: NEUROIMAGE
影响因子: 5.7
作者:
Friston, Karl J.;Mattout, Jeremie;Penny, Will
通讯作者: Penny, Will
DOI: 10.1371/journal.pone.0006421
发表时间: 2009-07-29
期刊: PloS one
影响因子: 3.7
作者:
Friston KJ;Daunizeau J;Kiebel SJ
通讯作者: Kiebel SJ
DOI: 10.3390/e23091220
发表时间: 2021-09-17
期刊: Entropy (Basel, Switzerland)
影响因子: --
作者:
Friston K;Heins C;Ueltzhöffer K;Da Costa L;Parr T
通讯作者: Parr T