1,566 research outputs found
Dark Patterns in the Design of Games
Game designers are typically regarded as advocates for players. However, a game creator’s interests may not align with the players’. We examine some of the ways in which those opposed interests can manifest in a game’s design. In particular, we examine those elements of a game’s design whose purpose can be argued as questionable and perhaps even unethical. Building upon earlier work in design patterns, we call these abstracted elements Dark Game Design Patterns. In this paper, we develop the concept of dark design patterns in games, present examples of such patterns, explore some of the subtleties involved in identifying them, and provide questions that can be asked to help guide in the specification and identification of future Dark Patterns. Our goal is not to criticize creators but rather to contribute to an ongoing discussion regarding the values in games and the role that designers and creators have in this process
The Laplace-Jaynes approach to induction
An approach to induction is presented, based on the idea of analysing the
context of a given problem into `circumstances'. This approach, fully Bayesian
in form and meaning, provides a complement or in some cases an alternative to
that based on de Finetti's representation theorem and on the notion of infinite
exchangeability. In particular, it gives an alternative interpretation of those
formulae that apparently involve `unknown probabilities' or `propensities'.
Various advantages and applications of the presented approach are discussed,
especially in comparison to that based on exchangeability. Generalisations are
also discussed.Comment: 38 pages, 1 figure. V2: altered discussion on some points, corrected
typos, added reference
Numerical Bayesian quantum-state assignment for a three-level quantum system. II. Average-value data with a constant, a Gaussian-like, and a Slater prior
This paper offers examples of concrete numerical applications of Bayesian
quantum-state assignment methods to a three-level quantum system. The
statistical operator assigned on the evidence of various measurement data and
kinds of prior knowledge is computed partly analytically, partly through
numerical integration (in eight dimensions) on a computer. The measurement data
consist in the average of outcome values of N identical von Neumann projective
measurements performed on N identically prepared three-level systems. In
particular the large-N limit will be considered. Three kinds of prior knowledge
are used: one represented by a plausibility distribution constant in respect of
the convex structure of the set of statistical operators; another one
represented by a prior studied by Slater, which has been proposed as the
natural measure on the set of statistical operators; the last prior is
represented by a Gaussian-like distribution centred on a pure statistical
operator, and thus reflecting a situation in which one has useful prior
knowledge about the likely preparation of the system. The assigned statistical
operators obtained with the first two kinds of priors are compared with the one
obtained by Jaynes' maximum entropy method for the same measurement situation.
In the companion paper the case of measurement data consisting in absolute
frequencies is considered.Comment: 10 pages, 4 figures. V2: added "Post scriptum" under Conclusions,
slightly changed Acknowledgements, and corrected some spelling error
Numerical Bayesian state assignment for a three-level quantum system. I. Absolute-frequency data; constant and Gaussian-like priors
This paper offers examples of concrete numerical applications of Bayesian
quantum-state-assignment methods to a three-level quantum system. The
statistical operator assigned on the evidence of various measurement data and
kinds of prior knowledge is computed partly analytically, partly through
numerical integration (in eight dimensions) on a computer. The measurement data
consist in absolute frequencies of the outcomes of N identical von Neumann
projective measurements performed on N identically prepared three-level
systems. Various small values of N as well as the large-N limit are considered.
Two kinds of prior knowledge are used: one represented by a plausibility
distribution constant in respect of the convex structure of the set of
statistical operators; the other represented by a Gaussian-like distribution
centred on a pure statistical operator, and thus reflecting a situation in
which one has useful prior knowledge about the likely preparation of the
system.
In a companion paper the case of measurement data consisting in average
values, and an additional prior studied by Slater, are considered.Comment: 23 pages, 14 figures. V2: Added an important note concerning
cylindrical algebraic decomposition and thanks to P B Slater, corrected some
typos, added reference
Interest Rates and Information Geometry
The space of probability distributions on a given sample space possesses
natural geometric properties. For example, in the case of a smooth parametric
family of probability distributions on the real line, the parameter space has a
Riemannian structure induced by the embedding of the family into the Hilbert
space of square-integrable functions, and is characterised by the Fisher-Rao
metric. In the nonparametric case the relevant geometry is determined by the
spherical distance function of Bhattacharyya. In the context of term structure
modelling, we show that minus the derivative of the discount function with
respect to the maturity date gives rise to a probability density. This follows
as a consequence of the positivity of interest rates. Therefore, by mapping the
density functions associated with a given family of term structures to Hilbert
space, the resulting metrical geometry can be used to analyse the relationship
of yield curves to one another. We show that the general arbitrage-free yield
curve dynamics can be represented as a process taking values in the convex
space of smooth density functions on the positive real line. It follows that
the theory of interest rate dynamics can be represented by a class of processes
in Hilbert space. We also derive the dynamics for the central moments
associated with the distribution determined by the yield curve.Comment: 20 pages, 3 figure
α2-macroglobulin and α1-inhibitor-3 mRNA expression in the rat liver after slow interleukin-1 stimulation
In this study we have investigated total fiver RNA and the expression of mRNA in the rat fiver in vivo after a slow stimulation of interleukin-1. A total dose of 4 μg interleukin-1β was administered via a subcutaneously implanted osmotic minipump over a period of 7 days. Plasma concentrations of α2-macroglobulin manifested a rapid increase, reaching a peak on day 2, while α1-inhibitor-3 manifested a marked initial decrease to 50% of the baseline level, followed by a tendency to increase again. For measurement of total RNA and specific mRNAs from the fiver, rats were sacrificed at different times during the experimental period. Total RNA peaked at 6 h, the level being approximately 60% higher than baseline value. Specific mRNA from the liver for α2-macroglobulin and α1-inhibitor-3 were quantified using laser densitometry on slot blots. The amounts measured during the experimental period agreed with the pattern of corresponding plasma protein levels. From barely detectable amounts at baseline, α2-macroglobulin mRNA peaked on day 1, and then declined. Levels of α1-inhibitor-3 mRNA manifested an initial increase at 3 h, but then declined and remained low until day 5 when there was a tendency towards an increase. It was concluded that the levels of plasma concentrations of α2-macroglobulin and α1-inhibitor-3 are mainly regulated at the protein synthesis level, and that long-term interleukin-1β release could not override the initial acute phase protein counteracting mechanism triggered
Quantum limits on phase-shift detection using multimode interferometers
Fundamental phase-shift detection properties of optical multimode
interferometers are analyzed. Limits on perfectly distinguishable phase shifts
are derived for general quantum states of a given average energy. In contrast
to earlier work, the limits are found to be independent of the number of
interfering modes. However, the reported bounds are consistent with the
Heisenberg limit. A short discussion on the concept of well-defined relative
phase is also included.Comment: 6 pages, 3 figures, REVTeX, uses epsf.st
Simultaneous minimum-uncertainty measurement of discrete-valued complementary observables
We have made the first experimental demonstration of the simultaneous minimum
uncertainty product between two complementary observables for a two-state
system (a qubit). A partially entangled two-photon state was used to perform
such measurements. Each of the photons carries (partial) information of the
initial state thus leaving a room for measurements of two complementary
observables on every member in an ensemble.Comment: 4 pages, 4 figures, REVTeX, submitted to PR
On the structure of the sets of mutually unbiased bases for N qubits
For a system of N qubits, spanning a Hilbert space of dimension d=2^N, it is
known that there exists d+1 mutually unbiased bases. Different construction
algorithms exist, and it is remarkable that different methods lead to sets of
bases with different properties as far as separability is concerned. Here we
derive the four sets of nine bases for three qubits, and show how they are
unitarily related. We also briefly discuss the four-qubit case, give the
entanglement structure of sixteen sets of bases,and show some of them, and
their interrelations, as examples. The extension of the method to the general
case of N qubits is outlined.Comment: 16 pages, 10 tables, 1 figur
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