Chance and Causation

2019 ◽  
pp. 214-236
Author(s):  
Carl Hoefer

Causality and objective probability are often linked. Some philosophers have tried to characterize objectively chancy setups as incomplete, partial causes of the various possible outcomes the setup may yield. Other philosophers have proposed probabilistic theories of causation, defining a cause c for an effect e as a factor whose presence raises the objective probability of e. Neither of these links is, overall, defensible. Nonetheless, it is clear that there is some link between causation and probability, as is shown with a simple vignette. Analyzing the vignette shows that one should link causation with subjective probability. It is proposed that the strongest general principle that links causation and probability is a Cause-Probability Principle (CPP), which says (roughly) that when an agent learns that a cause c for an effect e has been introduced or put into action, then her subjective probability for the occurrence of e should be at least as high as it was beforehand.

Author(s):  
John L. Pollock

Probability theorists divide into two camps-the proponents of subjective probability and the proponents of objective probability. Opinion has it that subjective probability has carried the day, but I think that such a judgment is premature. I have argued elsewhere that there are deep incoherencies in the notion of subjective probability. Accordingly, I find myself in the camp of objective probability. The consensus is, however, that the armies of objective probability are in even worse disarray. The purpose of this book is to construct a theory of objective probability that rectifies that. Such a theory must explain the meaning of objective probability, show how we can discover the values of objective probabilities, clarify their use in decision theory, and demonstrate how they can be used for epistemological purposes. The theory of nomic probability aims to do all that. This book has two main objectives. First, it will propose a general theory of objective probability. Second, it will, in a sense to be explained, propose a solution to the problem of induction. These two goals are intimately connected. I will argue that a solution to the problem of induction is forthcoming, ultimately, from an analysis of probabilistic reasoning. Under some circumstances, probabilistic reasoning justifies us in drawing non-probabilistic conclusions, and this kind of reasoning underlies induction. Conversely, an essential part of understanding probability consists of providing an account of how we can ascertain the values of probabilities, and the most fundamental way of doing that is by using a species of induction. In statistical induction we observe the relative frequency (the proportion) of A's in a limited sample of B's, and then infer that the probability of a B being an A is approximately the same as that relative frequency. To provide philosophical foundations for probability we must, among other things, explain precisely how statistical induction works and what justifies it. Probability is important both in and out of philosophy. Much of the reasoning of everyday life is probabilistic. We look at the clouds and judge whether it is going to rain by considering how often clouds like that have spawned rain in the past.


Systems ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 46 ◽  
Author(s):  
Thomas Monroe ◽  
Mario Beruvides ◽  
Víctor Tercero-Gómez

The uncertainty, or entropy, of an atom of an ideal gas being in a certain energy state mirrors the way people perceive uncertainty in the making of decisions, uncertainty that is related to unmeasurable subjective probability. It is well established that subjects evaluate risk decisions involving uncertain choices using subjective probability rather than objective, which is usually calculated using empirically derived decision weights, such as those described in Prospect Theory; however, an exact objective–subjective probability relationship can be derived from statistical mechanics and information theory using Kullback–Leibler entropy divergence. The resulting Entropy Decision Risk Model (EDRM) is based upon proximity or nearness to a state and is predictive rather than descriptive. A priori EDRM, without factors or corrections, accurately aligns with the results of prior decision making under uncertainty (DMUU) studies, including Prospect Theory and others. This research is a first step towards the broader effort of quantifying financial, programmatic, and safety risk decisions in fungible terms, which applies proximity (i.e., subjective probability) with power utility to evaluate choice preference of gains, losses, and mixtures of the two in terms of a new parameter referred to as Prospect. To facilitate evaluation of the EDRM against prior studies reported in terms of the percentage of subjects selecting a choice, the Percentage Evaluation Model (PEM) is introduced to convert choice value results into subject response percentages, thereby permitting direct comparison of a utility model for the first time.


1989 ◽  
Vol 64 (1) ◽  
pp. 243-249 ◽  
Author(s):  
Yoshiaki Nakajima ◽  
Hirohiko Ohta

The developmental change in subjective probability during adolescence, an important period for establishing the probability concept, was investigated. 75 Japanese adolescents, from 12 to 23 yr. of age, were asked to make probability judgments for a lottery under 15 conditions. Analysis showed that with increase in age their subjective probability came closer to the objective probability. Discussion of these results took into consideration recent studies on the development of the concept of probability.


Author(s):  
Aditya Akundi ◽  
Milad Zarei ◽  
Eric D Smith

Modern instances of disease emergence have shown that human subjective reactions to a novel disease can be as important as the objective reality of the disease spread. Therefore, this work introduces human cognitive heuristics and biases into epidemiological modeling. Human subjective perception and reaction to the presence of the disease is represented in the difference between the objective and subjective probability of contagion. It is assumed that humans within a disease spread situation will have either limited or full information about the objective probability of contagion. From this information, humans subjectively react, forming a subjective assessment of probability of contagion. Although the translation from the objective to subjective probability of contagion is rooted in a biological basis, the translation has been adequately determined by previous research in Prospect theory as developed by Daniel Kahneman and Amos Tversky. The formulation of Lotka-Volterra epidemiology models with parameters for perceived probability of contagion was followed by numerical experimentation and sensitivity analysis that determined values of parameters that create cyclic population behavior, whether growing or dampened, as well as acyclic behavior. The results show that the model is capable of capturing stable as well as unstable behavior, and is able to model key epidemiological disease behaviors and states, such as epidemic and endemic conditions.


2013 ◽  
Author(s):  
Aditya Akundi ◽  
Milad Zarei ◽  
Eric D Smith

Modern instances of disease emergence have shown that human subjective reactions to a novel disease can be as important as the objective reality of the disease spread. Therefore, this work introduces human cognitive heuristics and biases into epidemiological modeling. Human subjective perception and reaction to the presence of the disease is represented in the difference between the objective and subjective probability of contagion. It is assumed that humans within a disease spread situation will have either limited or full information about the objective probability of contagion. From this information, humans subjectively react, forming a subjective assessment of probability of contagion. Although the translation from the objective to subjective probability of contagion is rooted in a biological basis, the translation has been adequately determined by previous research in Prospect theory as developed by Daniel Kahneman and Amos Tversky. The formulation of Lotka-Volterra epidemiology models with parameters for perceived probability of contagion was followed by numerical experimentation and sensitivity analysis that determined values of parameters that create cyclic population behavior, whether growing or dampened, as well as acyclic behavior. The results show that the model is capable of capturing stable as well as unstable behavior, and is able to model key epidemiological disease behaviors and states, such as epidemic and endemic conditions.


2021 ◽  
Author(s):  
Jintong Liu ◽  
Jing Huang ◽  
Lei Zhang ◽  
Jianping Lei

We review the general principle of the design and functional modulation of nanoscaled MOF heterostructures, and biomedical applications in enhanced therapy.


2019 ◽  
Vol 62 (5) ◽  
pp. 1243-1257 ◽  
Author(s):  
Peggy Pik Ki Mok ◽  
Holly Sze Ho Fung ◽  
Vivian Guo Li

Purpose Previous studies showed early production precedes late perception in Cantonese tone acquisition, contrary to the general principle that perception precedes production in child language. How tone production and perception are linked in 1st language acquisition remains largely unknown. Our study revisited the acquisition of tone in Cantonese-speaking children, exploring the possible link between production and perception in 1st language acquisition. Method One hundred eleven Cantonese-speaking children aged between 2;0 and 6;0 (years;months) and 10 adolescent reference speakers participated in tone production and perception experiments. Production materials with 30 monosyllabic words were transcribed in filtered and unfiltered conditions by 2 native judges. Perception accuracy was based on a 2-alternative forced-choice task with pictures covering all possible tone pair contrasts. Results Children's accuracy of production and perception of all the 6 Cantonese tones was still not adultlike by age 6;0. Both production and perception accuracies matured with age. A weak positive link was found between the 2 accuracies. Mother's native language contributed to children's production accuracy. Conclusions Our findings show that production and perception abilities are associated in tone acquisition. Further study is needed to explore factors affecting production accuracy in children. Supplemental Material https://doi.org/10.23641/asha.7960826


1971 ◽  
Author(s):  
Barry R. Schlenker ◽  
Robert Brown ◽  
James T. Tedeschi

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