Reason, causation and compatibility with the phenomena

'Reason, Causation and Compatibility with the Phenomena' strives to give answers to the philosophical problem of the interplay between realism, explanation and experience. This book is a compilation of essays that recollect significant conceptions of rival terms such as determinism and freedom, reason and appearance, power and knowledge. This title discusses the progress made in epistemology and natural philosophy, especially the steps that led from the ancient theory of atomism to the modern quantum theory, and from mathematization to analytic philosophy. Moreover, it provides possible gateways from modern deadlocks of theory either through approaches to consciousness or through historical critique of intellectual authorities. This work will be of interest to those either researching or studying in colleges and universities, especially in the departments of philosophy, history of science, philosophy of science, philosophy of physics and quantum mechanics, history of ideas and culture. Greek and Latin Literature students and instructors may also find this book to be both a fascinating and valuable point of reference

Quantitative Verification: Formal Guarantees for Timeliness, Reliability and Performance

Computerised systems appear in almost all aspects of our daily lives, often in safety-critical scenarios such as embedded control systems in cars and aircraft or medical devices such as pacemakers and sensors. We are thus increasingly reliant on these systems working correctly, despite often operating in unpredictable or unreliable environments. Designers of such devices need ways to guarantee that they will operate in a reliable and efficient manner. Quantitative verification is a technique for analysing quantitative aspects of a system's design, such as timeliness, reliability or performance. It applies formal methods, based on a rigorous analysis of a mathematical model of the system, to automatically prove certain precisely specified properties, e.g. ``the airbag will always deploy within 20 milliseconds after a crash'' or ``the probability of both sensors failing simultaneously is less than 0.001''. The ability to formally guarantee quantitative properties of this kind is beneficial across a wide range of application domains. For example, in safety-critical systems, it may be essential to establish credible bounds on the probability with which certain failures or combinations of failures can occur. In embedded control systems, it is often important to comply with strict constraints on timing or resources. More generally, being able to derive guarantees on precisely specified levels of performance or efficiency is a valuable tool in the design of, for example, wireless networking protocols, robotic systems or power management algorithms, to name but a few. This report gives a short introduction to quantitative verification, focusing in particular on a widely used technique called model checking, and its generalisation to the analysis of quantitative aspects of a system such as timing, probabilistic behaviour or resource usage. The intended audience is industrial designers and developers of systems such as those highlighted above who could benefit from the application of quantitative verification,but lack expertise in formal verification or modelling

Gatekeepers and lock masters: the control of access in the Neo-Assyrian palaces

Book description: This volume is intended as a tribute to the memory of the Sumerologist Jeremy Black, who died in 2004. The Sumerian phrase, ‘Your praise is sweet’ is commonly addressed to a deity at the close of a work of Sumerian literature. The scope of the thirty contributions, from Sumerology to the nineteenth-century rediscovery of Mesopotamia, is testament to Jeremy’s own wide-ranging interests and to his ability to forge scholarly connections and friendships among all who shared his interest in ancient Iraq

Come back Marshall, all is forgiven? : Complexity, evolution, mathematics and Marshallian exceptionalism

Marshall was the great synthesiser of neoclassical economics. Yet with his qualified assumption of self-interest, his emphasis on variation in economic evolution and his cautious attitude to the use of mathematics, Marshall differs fundamentally from other leading neoclassical contemporaries. Metaphors inspire more specific analogies and ontological assumptions, and Marshall used the guiding metaphor of Spencerian evolution. But unfortunately, the further development of a Marshallian evolutionary approach was undermined in part by theoretical problems within Spencer's theory. Yet some things can be salvaged from the Marshallian evolutionary vision. They may even be placed in a more viable Darwinian framework.Peer reviewedFinal Accepted Versio

Towards Machine Wald

The past century has seen a steady increase in the need of estimating and predicting complex systems and making (possibly critical) decisions with limited information. Although computers have made possible the numerical evaluation of sophisticated statistical models, these models are still designed \emph{by humans} because there is currently no known recipe or algorithm for dividing the design of a statistical model into a sequence of arithmetic operations. Indeed enabling computers to \emph{think} as \emph{humans} have the ability to do when faced with uncertainty is challenging in several major ways: (1) Finding optimal statistical models remains to be formulated as a well posed problem when information on the system of interest is incomplete and comes in the form of a complex combination of sample data, partial knowledge of constitutive relations and a limited description of the distribution of input random variables. (2) The space of admissible scenarios along with the space of relevant information, assumptions, and/or beliefs, tend to be infinite dimensional, whereas calculus on a computer is necessarily discrete and finite. With this purpose, this paper explores the foundations of a rigorous framework for the scientific computation of optimal statistical estimators/models and reviews their connections with Decision Theory, Machine Learning, Bayesian Inference, Stochastic Optimization, Robust Optimization, Optimal Uncertainty Quantification and Information Based Complexity.Comment: 37 page

A Grassmann integral equation

The present study introduces and investigates a new type of equation which is called Grassmann integral equation in analogy to integral equations studied in real analysis. A Grassmann integral equation is an equation which involves Grassmann integrations and which is to be obeyed by an unknown function over a (finite-dimensional) Grassmann algebra G_m. A particular type of Grassmann integral equations is explicitly studied for certain low-dimensional Grassmann algebras. The choice of the equation under investigation is motivated by the effective action formalism of (lattice) quantum field theory. In a very general setting, for the Grassmann algebras G_2n, n = 2,3,4, the finite-dimensional analogues of the generating functionals of the Green functions are worked out explicitly by solving a coupled system of nonlinear matrix equations. Finally, by imposing the condition G[{\bar\Psi},{\Psi}] = G_0[{\lambda\bar\Psi}, {\lambda\Psi}] + const., 0<\lambda\in R (\bar\Psi_k, \Psi_k, k=1,...,n, are the generators of the Grassmann algebra G_2n), between the finite-dimensional analogues G_0 and G of the (``classical'') action and effective action functionals, respectively, a special Grassmann integral equation is being established and solved which also is equivalent to a coupled system of nonlinear matrix equations. If \lambda \not= 1, solutions to this Grassmann integral equation exist for n=2 (and consequently, also for any even value of n, specifically, for n=4) but not for n=3. If \lambda=1, the considered Grassmann integral equation has always a solution which corresponds to a Gaussian integral, but remarkably in the case n=4 a further solution is found which corresponds to a non-Gaussian integral. The investigation sheds light on the structures to be met for Grassmann algebras G_2n with arbitrarily chosen n.Comment: 58 pages LaTeX (v2: mainly, minor updates and corrections to the reference section; v3: references [4], [17]-[21], [39], [46], [49]-[54], [61], [64], [139] added

The sources of Mill's views of ratiocination and induction

Steffen Ducheyne and John P. McCaskey (2014). “The Sources of Mill’s Views of Ratiocination and Induction,” in: Antis Loizides (ed.), John Stuart Mill’s ‘A System of Logic’: A Critical Guide (London, Routledge), pp. 63-8

The Biopolitical Economy of Anti-Essentialism

If we are to understand the nature of the relationship between a culture and its economy it is necessary to trace out the logic that informs the apparently disparate currents that make up that culture and its economy. There are any number of loci by reference to which this relationship might be discerned, but none are so important or profound, or for that matter so telling, than our body. Following on from two previous articles this essay approaches the subject by way of Foucault’s understanding of the ‘biopolitical’.[1] Through the issues of sexuality and eugenics we see how the logic informing early modern liberal philosophy worked itself out, coming to its full realisation in what is today referred to as ‘anti-essentialism’. The rise of anti-essentialism is concomitant with, if not identical with, the rise of capitalism proper. Anti-essentialism, both as a cultural and economic phenomena, is necessary for the rise to global dominance of capitalism. Although anti-essentialism is often thought of in terms of postmodernism and performance theory something of its logic was understood in the early modern period. And it was so by way of opposition to the growing defence and acceptance of free-market economics, which acceptance went hand in glove with a free market in credit and debt, which is to say in the liberalisation of anti-usury laws

Creating the Royal Society's Sylvester Medal

Following the death of James Joseph Sylvester in 1897, contributions were collected in order to mark his life and work by a suitable memorial. This initiative resulted in the Sylvester Medal, which is awarded triennially by the Royal Society for the encouragement of research into pure mathematics. Ironically the main advocate for initiating this medal was not a fellow mathematician but the chemist and naturalist Raphael Meldola. Religion, not mathematics, provided the link between Meldola and Sylvester; they were among the very few Jewish Fellows of the Royal Society. This paper focuses primarily on the politics of the Anglo-Jewish community and why it, together with a number of scientists and mathematicians, supported Meldola in creating the Sylvester Medal