29,360 research outputs found
Computable Rationality, NUTS, and the Nuclear Leviathan
This paper explores how the Leviathan that projects power through nuclear arms exercises a unique nuclearized sovereignty. In the case of nuclear superpowers, this sovereignty extends to wielding the power to destroy human civilization as we know it across the globe. Nuclearized sovereignty depends on a hybrid form of power encompassing human decision-makers in a hierarchical chain of command, and all of the technical and computerized functions necessary to maintain command and control at every moment of the sovereign's existence: this sovereign power cannot sleep. This article analyzes how the form of rationality that informs this hybrid exercise of power historically developed to be computable. By definition, computable rationality must be able to function without any intelligible grasp of the context or the comprehensive significance of decision-making outcomes. Thus, maintaining nuclearized sovereignty necessarily must be able to execute momentous life and death decisions without the type of sentience we usually associate with ethical individual and collective decisions
Some Remarks about the Complexity of Epidemics Management
Recent outbreaks of Ebola, H1N1 and other infectious diseases have shown that
the assumptions underlying the established theory of epidemics management are
too idealistic. For an improvement of procedures and organizations involved in
fighting epidemics, extended models of epidemics management are required. The
necessary extensions consist in a representation of the management loop and the
potential frictions influencing the loop. The effects of the non-deterministic
frictions can be taken into account by including the measures of robustness and
risk in the assessment of management options. Thus, besides of the increased
structural complexity resulting from the model extensions, the computational
complexity of the task of epidemics management - interpreted as an optimization
problem - is increased as well. This is a serious obstacle for analyzing the
model and may require an additional pre-processing enabling a simplification of
the analysis process. The paper closes with an outlook discussing some
forthcoming problems
Rationality and the Foundations of Positive Political Theory
In this paper, we discuss and debunk the four most common critiques of the rational choice research program (which we prefer to call Positive Political Theory) by explaining and advocating its foundations: the rationality assumption, component analysis (abstraction), strategic behavior, and theory building, in turn. We argue that the rationality assumption and component analysis, properly understood, can be seen to underlie all social science, despite the protestations of critics. We then discuss the two ways that PPT most clearly contributes to political science (i.e., what distinguishes it from other research programs), namely the introduction of strategic behavior (people do not just act; they interact) and PPT’s more careful attention to the theory-building step within the scientific method. We explain the roles of theory- building and of empirical “testing,” respectively, in scientific inquiry, and the criteria by which theories should and should not be judged
A model of adaptive decision making from representation of information environment by quantum fields
We present the mathematical model of decision making (DM) of agents acting in
a complex and uncertain environment (combining huge variety of economical,
financial, behavioral, and geo-political factors). To describe interaction of
agents with it, we apply the formalism of quantum field theory (QTF). Quantum
fields are of the purely informational nature. The QFT-model can be treated as
a far relative of the expected utility theory, where the role of utility is
played by adaptivity to an environment (bath). However, this sort of
utility-adaptivity cannot be represented simply as a numerical function. The
operator representation in Hilbert space is used and adaptivity is described as
in quantum dynamics. We are especially interested in stabilization of solutions
for sufficiently large time. The outputs of this stabilization process,
probabilities for possible choices, are treated in the framework of classical
DM. To connect classical and quantum DM, we appeal to Quantum Bayesianism
(QBism). We demonstrate the quantum-like interference effect in DM which is
exhibited as a violation of the formula of total probability and hence the
classical Bayesian inference scheme.Comment: in press in Philosophical Transactions
Socio-hydrological modelling: a review asking “why, what and how?”
Interactions between humans and the environment are occurring on a scale that
has never previously been seen; the scale of human interaction with the water
cycle, along with the coupling present between social and hydrological
systems, means that decisions that impact water also impact people. Models
are often used to assist in decision-making regarding hydrological systems,
and so in order for effective decisions to be made regarding water resource
management, these interactions and feedbacks should be accounted for in
models used to analyse systems in which water and humans interact. This paper
reviews literature surrounding aspects of socio-hydrological modelling. It
begins with background information regarding the current state of
socio-hydrology as a discipline, before covering reasons for modelling and
potential applications. Some important concepts that underlie
socio-hydrological modelling efforts are then discussed, including ways of
viewing socio-hydrological systems, space and time in modelling, complexity,
data and model conceptualisation. Several modelling approaches are described,
the stages in their development detailed and their applicability to
socio-hydrological cases discussed. Gaps in research are then highlighted to
guide directions for future research. The review of literature suggests that
the nature of socio-hydrological study, being interdisciplinary, focusing on
complex interactions between human and natural systems, and dealing with long
horizons, is such that modelling will always present a challenge; it is,
however, the task of the modeller to use the wide range of tools afforded to
them to overcome these challenges as much as possible. The focus in
socio-hydrology is on understanding the human–water system in a holistic
sense, which differs from the problem solving focus of other water management
fields, and as such models in socio-hydrology should be developed with a view
to gaining new insight into these dynamics. There is an essential choice that
socio-hydrological modellers face in deciding between representing individual
system processes or viewing the system from a more abstracted level and
modelling it as such; using these different approaches has implications for
model development, applicability and the insight that they are capable of
giving, and so the decision regarding how to model the system requires
thorough consideration of, among other things, the nature of understanding
that is sought
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