scholarly journals Representation Lost: The Case for a Relational Interpretation of Quantum Mechanics

Entropy ◽  
2018 ◽  
Vol 20 (12) ◽  
pp. 975 ◽  
Author(s):  
Raffael Krismer
Keyword(s):  
Thought Experiment ◽  
Dynamical Evolution ◽  
Bayesian Probability ◽  
Special Focus ◽  
Probability Models ◽  
Classical Probability ◽  
Unitary Evolution ◽  
Relative Information ◽  
Mechanical Analogue ◽  
Argument Proceeds

Contemporary non-representationalist interpretations of the quantum state (especially QBism, neo-Copenhagen views, and the relational interpretation) maintain that quantum states codify observer-relative information. This paper provides an extensive defense of such views, while emphasizing the advantages of, specifically, the relational interpretation. The argument proceeds in three steps: (1) I present a classical example (which exemplifies the spirit of the relational interpretation) to illustrate why some of the most persistent charges against non-representationalism have been misguided. (2) The special focus is placed on dynamical evolution. Non-representationalists often motivate their views by interpreting the collapse postulate as the quantum mechanical analogue of Bayesian probability updating. However, it is not clear whether one can also interpret the Schrödinger equation as a form of rational opinion updating. Using results due to Hughes & van Fraassen as well as Lisi, I argue that unitary evolution has a counterpart in classical probability theory: in both cases (quantum and classical) probabilities relative to a non-participating observer evolve according to an entropy maximizing principle (and can be interpreted as rational opinion updating). (3) Relying on a thought-experiment by Frauchiger and Renner, I discuss the differences between quantum and classical probability models.

scholarly journals Brain in a Vat or Body in a World: Brainbound Versus Enactive View of Experience

2017 ◽  
Author(s):  
Evan Thompson ◽  
Diego Cosmelli
Keyword(s):  
Thought Experiment ◽  
The Body ◽  
Careful Examination ◽  
Living Body ◽  
The World ◽  
Neuronal Processes ◽  
Argument Proceeds ◽  
The Brain ◽  
Brain In A Vat ◽  
Embodied Agent

We argue that the minimal biological requirements for consciousness include a living body, not just neuronal processes in the skull. Our argument proceeds by reconsidering the brain-in-a-vat thought experiment. Careful examination of this thought experiment indicates that the null hypothesis is that any adequately functional “vat” would be a surrogate body, that is, that the so-called vat would be no vat at all, but rather an embodied agent in the world. Thus, what the thought experiment actually shows is that the brain and body are so deeply entangled, structurally and dynamically, that they are explanatorily inseparable. Such entanglement implies that we cannot understand consciousness by considering only the activity of neurons apart from the body, and hence we have good explanatory grounds for supposing that the minimal realizing system forconsciousness includes the body and not just the brain. In this way, we put the brain-in-a-vat thought experiment to a new use, one that supports the “enactive” view that consciousness is a life-regulation process of the wholeorganism interacting with its environment.

Unjustified Retribution

1993 ◽  
Vol 27 (1-2) ◽  
pp. 50-58 ◽  
Author(s):  
Dudley Knowles
Keyword(s):  
Thought Experiment ◽  
Moral Worth ◽  
Sufficient Condition ◽  
Necessary And Sufficient Condition ◽  
Begging The Question ◽  
Retributive Punishment ◽  
Argument Proceeds ◽  
Necessary And Sufficient

In a number of related papers Michael S. Moore has advanced a powerful theory of retributive punishment. The position as stated is simple: “retributivism is the view that we ought to punish offenders because and only because they deserve to be punished”. Desert is a necessary and sufficient condition for just punishment. However simple and straightforward the view, it still needs to be defended and Moore has been energetic in defending his corner against traditional objections and against replies that his account has attracted since first publication. His latest effort invites readers to pursue these problems in still greater depth. This is an invitation I am happy to accept. First I want to reexamine the charge that there is circularity in his account and second, I want to look more closely at the intuitions which ground his acceptance of the principle of desert.One worrying thought, for Moore, is that he may be begging the question. His argument proceeds by inviting us to consider a range of cases. In “The Moral Worth of Retribution” the focus is on a couple of savage murders. In “Justifying Retributivism” we are asked to practice Kant's thought-experiment: how should we deal with the last murderer before we leave the island; and ponder the fate of Dostoyevsky's nobleman who set his dogs to tear a child to pieces.

Quantum probability, choice in large worlds, and the statistical structure of reality

2013 ◽  
Vol 36 (3) ◽  
pp. 305-306
Author(s):  
Don Ross ◽  
James Ladyman
Keyword(s):  
Relative Risk ◽  
Statistical Processing ◽  
Quantum Probability ◽  
Probability Models ◽  
Statistical Structure ◽  
Classical Probability ◽  
Relative Structure ◽  
The Brain ◽  
The Universe

AbstractClassical probability models of incentive response are inadequate in “large worlds,” where the dimensions of relative risk and the dimensions of similarity in outcome comparisons typically differ. Quantum probability models for choice in large worlds may be motivated pragmatically – there is no third theory – or metaphysically: statistical processing in the brain adapts to the true scale-relative structure of the universe.

On stochastic models in biology and medicine

2020 ◽  
Vol 13 (08) ◽  
pp. 2050168
Author(s):  
Iveta Nikolova
Keyword(s):  
Probability Theory ◽  
Autoimmune Disease ◽  
Stochastic Models ◽  
Initial Conditions ◽  
Living Systems ◽  
Biological Processes ◽  
Probability Models ◽  
Deterministic Models ◽  
Classical Probability ◽  
Basic Concepts

Stochastic models along with deterministic models are successfully used for mathematical description of biological processes. They apply knowledge from probability theory and mathematical statistics to analyze specific characteristics of living systems. The paper is devoted to some stochastic models of various phenomena in biology and medicine. Basic concepts and definitions used in classical probability models are considered and illustrated by several examples with solutions. The stochastic kinetic modeling approach is described. A new kinetic model of autoimmune disease is presented. It is a system of nonlinear partial integro-differential equations supplemented by corresponding initial conditions. The modeling problem is solved computationally.

If quantum probability = classical probability + bounded cognition; is this good, bad, or unnecessary?

2013 ◽  
Vol 36 (3) ◽  
pp. 304-305
Author(s):  
Tim Rakow
Keyword(s):  
Probability Theory ◽  
Probabilistic Models ◽  
Current Knowledge ◽  
Quantum Probability ◽  
Model Specification ◽  
Probability Models ◽  
Classical Probability ◽  
Classical Probability Theory ◽  
Knowledge States

AbstractQuantum probability models may supersede existing probabilistic models because they account for behaviour inconsistent with classical probability theory that are attributable to normal limitations of cognition. This intriguing position, however, may overstate weaknesses in classical probability theory by underestimating the role of current knowledge states and may under-employ available knowledge about the limitations of cognitive processes. In addition, flexibility in model specification has risks for the use of quantum probability.

Sonar Map Construction for Ubiquitous Robotic System Using a Footprint Association Filter

2007 ◽  
Author(s):  
Yu-Cheol Lee ◽  
Wonpil Yu ◽  
Jong-Hwan Lim ◽  
Wan Kyun Chung ◽  
Dong-Woo Cho
Keyword(s):  
Mobile Robots ◽  
Home Environment ◽  
Specular Reflection ◽  
Autonomous Mobile Robots ◽  
Bayesian Probability ◽  
Probability Models ◽  
Probability Map ◽  
Grid Map ◽  
Map Construction ◽  
Data Points

This paper presents a method for building a probability grid map for autonomous mobile robots with ultrasonic sensors using a footprint association filter (FAF). The method is based on evaluating the possibility that the acquired sonar data are all reflected by the same object. The FAF is able to associate data points with each other. Data affected by specular reflection are not likely to be associated with the same object, so they are excluded from the data cluster by the FAF, thereby improving the reliability of the data used for the probability grid map. Since the corrupted data are not used to update the probability map, it is possible to build a good quality grid map even in a specular environment. The FAF was applied to the Bayesian probability models, which are typical models used to build grid maps, to verify its effectiveness. Experimental results were also obtained using a mobile robot in a ubiquitous home environment.

scholarly journals What Is Rational and Irrational in Human Decision Making

2021 ◽  
Vol 3 (1) ◽  
pp. 242-252
Author(s):  
Emmanuel M. Pothos ◽  
Oliver J. Waddup ◽  
Prince Kouassi ◽  
James M. Yearsley
Keyword(s):  
Probability Theory ◽  
Quantum Theory ◽  
Cognitive Theory ◽  
Cognitive Models ◽  
Probability Models ◽  
Classical Probability ◽  
Important Place ◽  
Classical Probability Theory ◽  
Human Decision ◽  
Normative Standard

There has been a growing trend to develop cognitive models based on the mathematics of quantum theory. A common theme in the motivation of such models has been findings which apparently challenge the applicability of classical formalisms, specifically ones based on classical probability theory. Classical probability theory has had a singularly important place in cognitive theory, because of its (in general) descriptive success but, more importantly, because in decision situations with low, equivalent stakes it offers a multiply justified normative standard. Quantum cognitive models have had a degree of descriptive success and proponents of such models have argued that they reveal new intuitions or insights regarding decisions in uncertain situations. However, can quantum cognitive models further benefit from normative justifications analogous to those for classical probability models? If the answer is yes, how can we determine the rational status of a decision, which may be consistent with quantum theory, but inconsistent with classical probability theory? In this paper, we review the proposal from Pothos, Busemeyer, Shiffrin, and Yearsley (2017), that quantum decision models benefit from normative justification based on the Dutch Book Theorem, in exactly the same way as models based on classical probability theory.

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