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This book presents interdisciplinary research in the science of
Human Cognition through mathematical and computational modeling and
simulation. Featuring new approaches developed by leading experts
in the field of cognitive science, it highlights the relevance and
depth of this important area of social sciences and its expanding
reach into the biological, physical, computational and mathematical
sciences. This contributed volume gathered the latest developments
as well as state-of-the art applications of cognitive modeling with
a genuine multidisciplinary approach to thinking, memory and
decision-making simulations. Topics include the Agent-based
Modeling in psychological Research, the Nyayasutra proof pattern,
Pheromone Trail Algorithm to model Analog Memory, Social Laser
Theory and applications, the challenges of probabilistic learning
for models of brain and behavior, Physicalistic perspective for the
emergence of cognition and computation, an analysis of the
conjunction fallacy as a fact, quantum modeling and causality in
physics and beyond, compositional vector semantics in spiking
neural networks, Optimality, Prototypes and Bilingualism,Â
the dimensionality of color perception. Given its scope and
approach, the book will benefit researchers and students of
computational social sciences, mathematics and its applications,
quantum physics.
The recent years have been characterized by stormy social protests
throughout the world. These protests have some commonalities, but
at the same time, their sociopolitical, psychological, and economic
contexts differ essentially. An important class of such protests is
known as color revolutions. The analysis of these events in social
and political literature is characterized by huge diversity of
opinions. We remark that the sociopolitical perturbations under
consideration are characterized by the cascade dynamics leading to
the exponential amplification of coherent social actions. In
quantum physics, such exponential and coherent amplification is the
basic feature of laser's functioning. ("Laser" is acronym for light
amplification by stimulated emission of radiation). In this book we
explore the theory of laser to model aforementioned waves of social
protests, from color revolutions to Brexit and Trump's election. We
call such social processes Stimulated Amplification of Social
Actions (SASA), but to keep closer to the analogy with physics we
merely operate with the term "social laser."
Composed of contributions from leading experts in quantum
foundations, this volume presents viewpoints on a number of complex
problems through informational, probabilistic, and mathematical
perspectives and features novel mathematical models of quantum and
subquantum phenomena. Rich with multi-disciplinary mathematical
content, this book includes applications of partial differential
equations in quantum field theory, differential geometry,
oscillatory processes and vibrations, and Feynman integrals for
quickly growing potential functions. Due to rapid growth in the
field in recent years, this volume aims to promote
interdisciplinary collaboration in the areas of quantum
probability, information, communication and foundation, and
mathematical physics. Many papers discuss complex yet novel
problems that depart from the mainstream of quantum physical
studies. Others devote explanation to fundamental problems of the
conventional quantum theory, including its mathematical formalism.
Overall, authors cover a diverse set of topics, including quantum
and classical field theory and oscillatory processing, quantum
mechanics from a Darwinian evolutionary perspective, and biological
applications of quantum theory. Together in one volume, these
essays will be useful to experts in the corresponding areas of
quantum theory. Theoreticians, experimenters, mathematicians, and
even philosophers in quantum physics and quantum probability and
information theory can consider this book a valuable resource.
Composed of contributions from leading experts in quantum
foundations, this volume presents viewpoints on a number of complex
problems through informational, probabilistic, and mathematical
perspectives and features novel mathematical models of quantum and
subquantum phenomena. Rich with multi-disciplinary mathematical
content, this book includes applications of partial differential
equations in quantum field theory, differential geometry,
oscillatory processes and vibrations, and Feynman integrals for
quickly growing potential functions. Due to rapid growth in the
field in recent years, this volume aims to promote
interdisciplinary collaboration in the areas of quantum
probability, information, communication and foundation, and
mathematical physics. Many papers discuss complex yet novel
problems that depart from the mainstream of quantum physical
studies. Others devote explanation to fundamental problems of the
conventional quantum theory, including its mathematical formalism.
Overall, authors cover a diverse set of topics, including quantum
and classical field theory and oscillatory processing, quantum
mechanics from a Darwinian evolutionary perspective, and biological
applications of quantum theory. Together in one volume, these
essays will be useful to experts in the corresponding areas of
quantum theory. Theoreticians, experimenters, mathematicians, and
even philosophers in quantum physics and quantum probability and
information theory can consider this book a valuable resource.
It is not intuitive to accept that there exists a link between
quantum physical systems and cognitive systems. However, recent
research has shown that cognitive systems and collective (social)
systems, including biology, exhibit uncertainty which can be
successfully modelled with quantum probability. The use of such
probability allows for the modelling of situations which typically
violate the laws of classical probability. The Palgrave Handbook of
Quantum Models in Social Science is is a unique volume that brings
together contributions from leading experts on key topics in this
new and emerging field. Completely self-contained, it begins with
an introductory section which gathers all the fundamental notions
required to be able to understand later chapters. The handbook then
moves on to address some of the latest research and applications
for quantum methods in social science disciplines, including
economics, politics and psychology. It begins with the issue of how
the quantum mechanical framework can be applied to economics.
Chapters devoted to this topic range from how Fisher information
can be argued to play a role in economics, to the foundations and
application of quantum game theory. The handbook then progresses in
considering how belief states can be updated with the theory of
quantum measurements (and also with more general methods). The
practical use of the Hilbert space (and Fock space) in decision
theory is then introduced, and open quantum systems are also
considered. The handbook also treats a model of neural oscillators
that reproduces some of the features of quantum cognition. Other
contributions delve into causal reasoning using quantum Bayes nets
and the role of quantum probability in modelling so called
affective evaluation. The handbook is rounded off with two chapters
which discuss the grand challenges which lie ahead of us. How can
the quantum formalism be justified in social science and is the
traditional quantum formalism too restrictive? Finally, a question
is posed: whether there is a necessary role for quantum
mathematical models to go beyond physics. This book will bring the
latest and most cutting edge research on quantum theory to social
science disciplines. Students and researchers across the
discipline, as well as those in the fields of physics and
mathematics will welcome this important addition to the literature.
This book examines information processing performed by bio-systems
at all scales: from genomes, cells and proteins to cognitive and
even social systems. It introduces a theoretical/conceptual
principle based on quantum information and non-Kolmogorov
probability theory to explain information processing phenomena in
biology as a whole. The book begins with an introduction followed
by two chapters devoted to fundamentals, one covering classical and
quantum probability, which also contains a brief introduction to
quantum formalism, and another on an information approach to
molecular biology, genetics and epigenetics. It then goes on to
examine adaptive dynamics, including applications to biology, and
non-Kolmogorov probability theory. Next, the book discusses the
possibility to apply the quantum formalism to model biological
evolution, especially at the cellular level: genetic and epigenetic
evolutions. It also presents a model of the epigenetic cellular
evolution based on the mathematical formalism of open quantum
systems. The last two chapters of the book explore foundational
problems of quantum mechanics and demonstrate the power of usage of
positive operator valued measures (POVMs) in biological science.
This book will appeal to a diverse group of readers including
experts in biology, cognitive science, decision making, sociology,
psychology, and physics; mathematicians working on problems of
quantum probability and information and researchers in quantum
foundations.
The present wave of interest in quantum foundations is caused by
the tremendous development of quantum information science and its
applications to quantum computing and quantum communication. It has
become clear that some of the difficulties encountered in
realizations of quantum information processing have roots at the
very fundamental level. To solve such problems, quantum theory has
to be reconsidered. This book is devoted to the analysis of the
probabilistic structure of quantum theory, probing the limits of
classical probabilistic representation of quantum phenomena.
This monograph presents recent developments of the theory of
algebraic dynamical systems and their applications to computer
sciences, cryptography, cognitive sciences, psychology, image
analysis, and numerical simulations. The most important
mathematical results presented in this book are in the fields of
ergodicity, p-adic numbers, and noncommutative groups. For students
and researchers working on the theory of dynamical systems,
algebra, number theory, measure theory, computer sciences,
cryptography, and image analysis.
This is the first fundamental book devoted to non-Kolmogorov
probability models. It provides a mathematical theory of negative
probabilities, with numerous applications to quantum physics,
information theory, complexity, biology and psychology. The book
also presents an interesting model of cognitive information reality
with flows of information probabilities, describing the process of
thinking, social, and psychological phenomena.
01/07 This title is now available from Walter de Gruyter. Please
see www.degruyter.com for more information. Like geometry,
probability can not be reduced to just one model to describe all
physical and biological phenomena. Each model has a restricted
range of applications. Quantum physics demonstrated that the use of
conventional probability models induces some paradoxes. Such
paradoxes can be resolved by using non-Kolmogorov probability
models, developed on the basis of purely classical interpretations
of probability: frequency and ensemble. Frequency models describe
violations of the law of large numbers. Ensemble models are models
with infinitely small probabilities. This is the first fundamental
book devoted to non-Kolmogorov probability models. It provides the
first mathematical theory of negative probabilities - with numerous
applications to quantum physics, information theory, complexity,
biology and psychology. Natural models with negative (frequency and
ensemble) probabilities are developed in the framework of so called
p-adic analysis. The book also contains an extremely interesting
model of cognitive information reality with flows of information
probabilities, describing the process of thinking, social and
psychological phenomena. This book will be of value and interest to
specialists in probability theory, statistics, functional analysis,
quantum physics and (partly) specialists in cognitive sciences and
psychology.
Recent years have been characterized by tremendous advances in
quantum information and communication, both theoretically and
experimentally. In addition, mathematical methods of quantum
information and quantum probability have begun spreading to other
areas of research, beyond physics. One exciting new possibility
involves applying these methods to information science and computer
science (without direct relation to the problems of creation of
quantum computers). The aim of this Special Volume is to encourage
scientists, especially the new generation (master and PhD
students), working in computer science and related mathematical
fields to explore novel possibilities based on the mathematical
formalisms of quantum information and probability. The contributing
authors, who hail from various countries, combine extensive quantum
methods expertise with real-world experience in application of
these methods to computer science. The problems considered chiefly
concern quantum information-probability based modeling in the
following areas: information foraging; interactive quantum
information access; deep convolutional neural networks; decision
making; quantum dynamics; open quantum systems; and theory of
contextual probability. The book offers young scientists (students,
PhD, postdocs) an essential introduction to applying the
mathematical apparatus of quantum theory to computer science,
information retrieval, and information processes.
Recent years have been characterized by tremendous advances in
quantum information and communication, both theoretically and
experimentally. In addition, mathematical methods of quantum
information and quantum probability have begun spreading to other
areas of research, beyond physics. One exciting new possibility
involves applying these methods to information science and computer
science (without direct relation to the problems of creation of
quantum computers). The aim of this Special Volume is to encourage
scientists, especially the new generation (master and PhD
students), working in computer science and related mathematical
fields to explore novel possibilities based on the mathematical
formalisms of quantum information and probability. The contributing
authors, who hail from various countries, combine extensive quantum
methods expertise with real-world experience in application of
these methods to computer science. The problems considered chiefly
concern quantum information-probability based modeling in the
following areas: information foraging; interactive quantum
information access; deep convolutional neural networks; decision
making; quantum dynamics; open quantum systems; and theory of
contextual probability. The book offers young scientists (students,
PhD, postdocs) an essential introduction to applying the
mathematical apparatus of quantum theory to computer science,
information retrieval, and information processes.
Written by world experts in the foundations of quantum mechanics
and its applications to social science, this book shows how
elementary quantum mechanical principles can be applied to
decision-making paradoxes in psychology and used in modelling
information in finance and economics. The book starts with a
thorough overview of some of the salient differences between
classical, statistical and quantum mechanics. It presents arguments
on why quantum mechanics can be applied outside of physics and
defines quantum social science. The issue of the existence of
quantum probabilistic effects in psychology, economics and finance
is addressed and basic questions and answers are provided. Aimed at
researchers in economics and psychology, as well as physics, basic
mathematical preliminaries and elementary concepts from quantum
mechanics are defined in a self-contained way.
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