Critical Notice of Kant's Transcendental Deduction, by Henry Allison. Oxford: Oxford University Press, 2015. Pp. Xv + 477.

In this paper we investigate three approaches to iterated contraction, namely: the Moderate (or Priority) contraction, the Natural (or Conservative) contraction, and the Lexicographic contraction. We characterise these three contraction functions using certain, arguably plausible, properties of an iterated contraction function. While we provide the characterisation of the first two contraction operations using rationality postulates of the standard variety for iterated contraction, we found doing the same for the Lexicographic contraction more challenging. We provide its characterisation using a variation of (...) Epistemic ranking function instead. (shrink)

R.A.Fisher introduced the fiducial argument as a means for obtaining something from nothing. He thought that on some occasions it was legitimate to obtain a posterior probability distribution over a range of simple statistical hypotheses without commitment to a prior distribution [4].H.Jeffreys thought he could tame Fisher by casting his argument in a Bayesian mold through a derivation of the fiducial posterior from a suitably constructed ignorance prior via Bayes’ theorem and conditionalization on the data of experimentation. According to Jeffreys, (...) Fisher was using something to obtain something after all ([7],pp.381-383).D.V.Lindley furthered the process of taming by specifying allegedly necessary and sufficient conditions for the consistency of fiducial reasoning in contexts of one parameter estimation with Bayesian requirements [14]. I. Hacking exploited Lindley’s result to supply his own ingenious method for taming Fisher([5],ch. 9).T.Seidenfeld has recently demonstrated that Lindley’s conditions are insufficient for consistency and that reconstructions like Jeffreys’ or Hacking’s lead to contradiction ([15], PP. 721-727). (shrink)

This is a brief review of issues over which Henry Kyburg and I differed concerning the requirement that full beliefs should be closed under deductive consequence.

This paper aims to make explicit the methodological conditions that should be satisfied for the Bayesian model to be used as a normative model of human probability judgment. After noticing the lack of a clear definition of Bayesianism in the psychological literature and the lack of justification for using it, a classic definition of subjective Bayesianism is recalled, based on the following three criteria: an epistemic criterion, a static coherence criterion and a dynamic coherence criterion. Then it is shown that (...) the adoption of this framework has two kinds of implications. The first one regards the methodology of the experimental study of probability judgment. The Bayesian framework creates pragmatic constraints on the methodology that are linked to the interpretation of, and the belief in, the information presented, or referred to, by an experimenter in order for it to be the basis of a probability judgment by individual participants. It is shown that these constraints have not been satisfied in the past, and the question of whether they can be satisfied in principle is raised and answered negatively. The second kind of implications consists of two limitations in the scope of the Bayesian model. They regard (1) the background of revision (the Bayesian model considers only revising situations but not updating situations), and (2) the notorious case of the null priors. In both cases Lewis’ rule is an appropriate alternative to Bayes’ rule, but its use faces the same operational difficulties. (shrink)

G.L.S. Shackle stood at the historic crossroads where the economics of Hayek and Keynes met. Shackle fused these opposing lines of thought in a macroeconomic theory that draws Keynesian conclusions from Austrian premises. In Shackle 's scheme of thought, the power to imagine alternative courses of action releases decision makers from the web of predictable causation. But the spontaneous and unpredictable choices that originate in the subjective and disparate orientations of individual agents deny us the possibility of rational expectations, and (...) therewith the logical coherence of market equilibrium over time. (shrink)

This article documents the history of the Allais paradox, and shows that underneath the many discussions of the various protagonists lay different, irreconcilable epistemological positions. Savage, like his mentor von Neumann and similar to economist Friedman, worked from an epistemology of generalized characterizations. Allais, on the other hand, like economists Samuelson and Baumol, started from an epistemology of exact descriptions in which every axiom was an empirical claim that could be refuted directly by observations. As a result, the two sides (...) failed to find a common ground. Only a few decades later was the now so-called Allais paradox rediscovered as an important precursor when a new behavioural economic subdiscipline started to adopt the epistemology of exact descriptions and its accompanying falsifications of rational choice theory. (shrink)

The paper studies first order extensions of classical systems of modal logic (see (Chellas, 1980, part III)). We focus on the role of the Barcan formulas. It is shown that these formulas correspond to fundamental properties of neighborhood frames. The results have interesting applications in epistemic logic. In particular we suggest that the proposed models can be used in order to study monadic operators of probability (Kyburg, 1990) and likelihood (Halpern-Rabin, 1987).

Certain ethical views hold that we should pay more attention, even exclusive attention, to the worst-case scenario. Prominent examples include Rawls's Difference Principle and the Precautionary Principle. These views can be anchored in formal principles of decision theory, in two different ways. On the one hand, they can rely on ambiguity-aversion: the idea that we cannot assign sharp probabilities to various scenarios, and that if we cannot assign sharp probabilities, we should decide pessimistically, as if the probabilities are unfavorable. On (...) the other hand, they can rely on risk-avoidance: the idea that we should pay more attention to worse scenarios, even when we can assign sharp probabilities. I distinguish these two foundations. I also show how they can be modified to support versions of these views that pay more but not exclusive attention to worst-case scenarios. Finally, I argue that risk-avoidance provides a superior foundation than ambiguity-aversion for the Difference Principle and the Precautionary Principle; in particular, it correctly identifies which ethical facts should matter to those who champion these principles. (shrink)

Suppose we want to do the most good we can with a particular sum of money, but we cannot be certain of the consequences of different ways of making use of it. This article explores how our attitudes towards risk and ambiguity bear on what we should do. It shows that risk-avoidance and ambiguity-aversion can each provide good reason to divide our money between various charitable organizations rather than to give it all to the most promising one. It also shows (...) how different attitudes towards risk and ambiguity affect whether we should give to an organization which does a small amount of good for certain or to one which does a large amount of good with some small or unknown probability. (shrink)

The conclusions derived by Keynes in his Treatise on Probability (1921) concerning induction, analogical reasoning, expectations formation and decision making, mirror and foreshadow the main conclusions of cognitive science and psychology.The problem of weight is studied within an economic context by examining the role it played in Keynes' applied philosophy work, The General Theory (1936). Keynes' approach is then reformulated as an optimal control approach to dealing with changes in information evaluation over time. Based on this analysis the problem of (...) inductive justification, from a societal perspective, is not, What can we rationally believe will occur in the economic future, given our past experiences? but Can we make the future so as to attain specific economic goals with practical certainty? An answer requires that restrictions be placed on the methodological individualist approach and the acceptance of a restricted holistic approach. (shrink)

Savage denied that Bayesian decision theory applies in large worlds. This paper proposes a minimal extension of Bayesian decision theory to a large-world context that evaluates an event E\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$E$$\end{document} by assigning it a number π\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi $$\end{document} that reduces to an orthodox probability for a class of measurable events. The Hurwicz criterion evaluates π\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi $$\end{document} (...) as a weighted arithmetic mean of its upper and lower probabilities, which we derive from the measurable supersets and subsets of E\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$E$$\end{document}. The ambiguity aversion reported in experiments on the Ellsberg paradox is then explained by assigning a larger weight to the lower probability of winning than to the upper probability. However, arguments are given here that would make anything but equal weights irrational when using the Hurwicz criterion. The paper continues by embedding the Hurwicz criterion in an extension of expected utility theory that we call expectant utility. (shrink)

Organization emerges as reality only through language. Transformation is such an emergence and it must get over the present context. A descriptive or implicative language fails to transcend the context. Linguistic suggestion of imageries and linguistic communion through imagination take departure from the present context and emerge as the new pleasurable transformed reality of organization. Linguistic holds the key to organizational transformation.

Various theories try to give accounts of how measures of this confidence do or ought to behave, both as far as the internal mental consistency of the agent as ...

Ranking theory is one of the salient formal representations of doxastic states. It differs from others in being able to represent belief in a proposition (= taking it to be true), to also represent degrees of belief (i.e. beliefs as more or less firm), and thus to generally account for the dynamics of these beliefs. It does so on the basis of fundamental and compelling rationality postulates and is hence one way of explicating the rational structure of doxastic states. Thereby (...) it provides foundations for accounts of defeasible or nonmonotonic reasoning. It has widespread applications in philosophy, it proves to be most useful in Artificial Intelligence, and it has started to find applications as a model of reasoning in psychology. (shrink)

"A Survey of Ranking Theory": The paper gives an up-to-date survey of ranking theory. It carefully explains the basics. It elaborates on the ranking theoretic explication of reasons and their balance. It explains the dynamics of belief statable in ranking terms and indicates how the ranks can thereby be measured. It suggests how the theory of Bayesian nets can be carried over to ranking theory. It indicates what it might mean to objectify ranks. It discusses the formal and the philosophical (...) aspects of the tight relation and the complementarity of ranks and probabilities. It closes with comparative remarks on predecessors and other philosophical proposals as well as formal models developed in AI. (shrink)