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In recent years, there has been a growing interest in the fields of
pattern recognition and machine vision in academia and industries.
New theories have been developed, with new design of technology and
systems in both hardware and software. They are widely applied to
our daily life to solve real problems in such diverse areas as
science, engineering, agriculture, e-commerce, education, robotics,
government, medicine, games and animation, medical imaging analysis
and diagnosis, military, and national security. The foundation of
all this field can be traced back to the late Prof. King-Sun Fu,
one of the founding fathers of pattern recognition, who, with
visionary insight founded the International Association for Pattern
Recognition around 1980. In the almost 30 years since then, the
world has witnessed the rapid growth and development of this field.
It is probably true to say that most people are affected by, or use
applications of pattern recognition in daily life. Today, on the
eve of 25th anniversary of the unfortunate and untimely passing of
Prof. Fu, we are proud to produce this volume of collected works
from world renowned professionals and experts in pattern
recognition and machine vision, in honor and memory of the late
Prof. King-Sun Fu. We hope this book will help promote further the
course, not only of fundamental principles, systems and
technologies, but also its vast range of applications to help in
solving problems in daily life. Contents Basic Foundations of
Pattern Recognition and Artificial Intelligence, Methodologies of
Machine Vision and Image Processing, Intelligent Pattern
Recognition Systems, 3-D Object Pattern Analysis, Modelling and
Simulation, Analysis of DNA Microarray Gene Expression Data based
on Pattern Recognition Methods, PRMV Applications.
This book addresses a number of questions from the perspective of
complex systems: How can we quantitatively understand the life
phenomena? How can we model life systems as complex bio-molecular
networks? Are there any methods to clarify the relationships among
the structures, dynamics and functions of bio-molecular networks?
How can we statistically analyse large-scale bio-molecular
networks? Focusing on the modeling and analysis of bio-molecular
networks, the book presents various sophisticated mathematical and
statistical approaches. The life system can be described using
various levels of bio-molecular networks, including gene regulatory
networks, and protein-protein interaction networks. It first
provides an overview of approaches to reconstruct various
bio-molecular networks, and then discusses the modeling and
dynamical analysis of simple genetic circuits, coupled genetic
circuits, middle-sized and large-scale biological networks,
clarifying the relationships between the structures, dynamics and
functions of the networks covered. In the context of large-scale
bio-molecular networks, it introduces a number of statistical
methods for exploring important bioinformatics applications,
including the identification of significant bio-molecules for
network medicine and genetic engineering. Lastly, the book
describes various state-of-art statistical methods for analysing
omics data generated by high-throughput sequencing. This book is a
valuable resource for readers interested in applying systems
biology, dynamical systems or complex networks to explore the truth
of nature.
This book addresses a number of questions from the perspective of
complex systems: How can we quantitatively understand the life
phenomena? How can we model life systems as complex bio-molecular
networks? Are there any methods to clarify the relationships among
the structures, dynamics and functions of bio-molecular networks?
How can we statistically analyse large-scale bio-molecular
networks? Focusing on the modeling and analysis of bio-molecular
networks, the book presents various sophisticated mathematical and
statistical approaches. The life system can be described using
various levels of bio-molecular networks, including gene regulatory
networks, and protein-protein interaction networks. It first
provides an overview of approaches to reconstruct various
bio-molecular networks, and then discusses the modeling and
dynamical analysis of simple genetic circuits, coupled genetic
circuits, middle-sized and large-scale biological networks,
clarifying the relationships between the structures, dynamics and
functions of the networks covered. In the context of large-scale
bio-molecular networks, it introduces a number of statistical
methods for exploring important bioinformatics applications,
including the identification of significant bio-molecules for
network medicine and genetic engineering. Lastly, the book
describes various state-of-art statistical methods for analysing
omics data generated by high-throughput sequencing. This book is a
valuable resource for readers interested in applying systems
biology, dynamical systems or complex networks to explore the truth
of nature.
This book focuses on the control of fractal behaviors in nonlinear
dynamics systems, addressing both the principles and purposes of
control. For fractals in different systems, it presents revealing
studies on the theory and applications of control, reflecting a
spectrum of different control methods used with engineering
technology. As such, it will benefit researchers, engineers, and
graduate students in fields of fractals, chaos, engineering, etc.
This book focuses on the control of fractal behaviors in nonlinear
dynamics systems, addressing both the principles and purposes of
control. For fractals in different systems, it presents revealing
studies on the theory and applications of control, reflecting a
spectrum of different control methods used with engineering
technology. As such, it will benefit researchers, engineers, and
graduate students in fields of fractals, chaos, engineering, etc.
This book is a collection of writings by active researchers in the
field of Artificial General Intelligence, on topics of central
importance in the field. Each chapter focuses on one theoretical
problem, proposes a novel solution, and is written in sufficiently
non-technical language to be understandable by advanced
undergraduates or scientists in allied fields. This book is the
very first collection in the field of Artificial General
Intelligence (AGI) focusing on theoretical, conceptual, and
philosophical issues in the creation of thinking machines. All the
authors are researchers actively developing AGI projects, thus
distinguishing the book from much of the theoretical cognitive
science and AI literature, which is generally quite divorced from
practical AGI system building issues. And the discussions are
presented in a way that makes the problems and proposed solutions
understandable to a wide readership of non-specialists, providing a
distinction from the journal and conference-proceedings literature.
The book will benefit AGI researchers and students by giving them a
solid orientation in the conceptual foundations of the field (which
is not currently available anywhere); and it would benefit
researchers in allied fields by giving them a high-level view of
the current state of thinking in the AGI field. Furthermore, by
addressing key topics in the field in a coherent way, the
collection as a whole may play an important role in guiding future
research in both theoretical and practical AGI, and in linking AGI
research with work in allied disciplines
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Artificial General Intelligence - 6th International Conference, AGI 2013, Beijing, China, July 31 -- August 3, 2013, Proceedings (Paperback, 2013 ed.)
Kai-Uwe Kuhnberger, Sebastian Rudolph, Pei Wang
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R1,429
Discovery Miles 14 290
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 6th
International Conference on Artificial General Intelligence, AGI
2013, held in Beijing, China, in July/August 2013. The 23 papers
(17 full papers, 3 technical communications, and 3 special session
papers) were carefully reviewed and selected from various
submissions. The volume collects the current research endeavors
devoted to develop formalisms, algorithms, and models, as well as
systems that are targeted at general intelligence. Similar to the
predecessor AGI conferences, researchers proposed different
methodologies and techniques in order to bridge the gap between
forms of specialized intelligence and general intelligence.
This book is a collection of writings by active researchers in the
field of Artificial General Intelligence, on topics of central
importance in the field. Each chapter focuses on one theoretical
problem, proposes a novel solution, and is written in sufficiently
non-technical language to be understandable by advanced
undergraduates or scientists in allied fields. This book is the
very first collection in the field of Artificial General
Intelligence (AGI) focusing on theoretical, conceptual, and
philosophical issues in the creation of thinking machines. All the
authors are researchers actively developing AGI projects, thus
distinguishing the book from much of the theoretical cognitive
science and AI literature, which is generally quite divorced from
practical AGI system building issues. And the discussions are
presented in a way that makes the problems and proposed solutions
understandable to a wide readership of non-specialists, providing a
distinction from the journal and conference-proceedings literature.
The book will benefit AGI researchers and students by giving them a
solid orientation in the conceptual foundations of the field (which
is not currently available anywhere); and it would benefit
researchers in allied fields by giving them a high-level view of
the current state of thinking in the AGI field. Furthermore, by
addressing key topics in the field in a coherent way, the
collection as a whole may play an important role in guiding future
research in both theoretical and practical AGI, and in linking AGI
research with work in allied disciplines
This book is the most comprehensive description of the
decades-long Non-Axiomatic Reasoning System (NARS) project,
including its philosophical foundation, methodological
consideration, conceptual design details, implications in the
related fields, and its similarities and differences to many
related works in cognitive science. While most current works in
Artificial Intelligence (AI) focus on individual aspects of
intelligence and cognition, NARS is designed and developed to
attack the AI problem as a whole.
This project is based on the belief that what we call intelligence
can be understood and reproduced as the capability of a system to
adapt to its environment while working with insufficient knowledge
and resources. According to this idea, a novel reasoning system is
designed, which challenges all the dominating theories in how such
a system should be built. The system carries out reasoning,
learning, categorizing, planning, decision making, etc., as
different facets of the same underlying process. This theory also
provides unified solutions to many problems in AI, logic,
psychology, and philosophy. This book is the most comprehensive
description of this decades-long project, including its
philosophical foundation, methodological consideration, conceptual
design details, its implications in the related fields, as well as
its similarities and differences to many related works in cognitive
sciences.
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Artificial General Intelligence - 9th International Conference, AGI 2016, New York, NY, USA, July 16-19, 2016, Proceedings (Paperback, 1st ed. 2016)
Bas Steunebrink, Pei Wang, Ben Goertzel
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R2,665
Discovery Miles 26 650
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 9th
International Conference on Artificial General Intelligence, AGI
2016, held in New York City, NY, USA, in July 2016 as part of HLAI
2016, the Joint Multi-Conference on Human-Level Artificial
Intelligence 2016. The 24 full papers, 2 short papers, and 10
poster papers presented were carefully reviewed and selected from
67 submissions. AGI research differs from the ordinary AI research
by stressing on the versatility and wholeness of intelligence, and
by carrying out the engineering practice according to an outline of
a system comparable to the human mind inSelf a certain sense.
This book provides a systematic and comprehensive description of
Non-Axiomatic Logic, which is the result of the author's research
for about three decades.Non-Axiomatic Logic is designed to provide
a uniform logical foundation for Artificial Intelligence, as well
as an abstract description of the "laws of thought" followed by the
human mind. Different from "mathematical" logic, where the focus is
the regularity required when demonstrating mathematical
conclusions, Non-Axiomatic Logic is an attempt to return to the
original aim of logic, that is, to formulate the regularity in
actual human thinking. To achieve this goal, the logic is designed
under the assumption that the system has insufficient knowledge and
resources with respect to the problems to be solved, so that the
"logical conclusions" are only valid with respect to the available
knowledge and resources. Reasoning processes according to this
logic covers cognitive functions like learning, planning, decision
making, problem solving, etc.This book is written for researchers
and students in Artificial Intelligence and Cognitive Science, and
can be used as a textbook for courses at graduate level, or
upper-level undergraduate, on Non-Axiomatic Logic.
Genomic DNA copy number alterations are key genetic events in the
initiation and progression of human cancers. Recent advance in the
technique of microarray comparative genomic hybridization (array
CGH) enables one to screen genome-wide for all possible regions
with DNA copy number alterations, such as chromosome gains and
losses, or localized amplifications and deletions. In this book, we
introduce two statistical methods addressing two different
questions for the data analysis of array CGH. The first
method---Cluster Along Chromosomes--- is developed for calling
gains and losses in CGH arrays. The second method--- Boosted PRIM
(Patient Rule Induction Method)--- is developed to search for
oncogenic pathways using array-CGH data. The performance of the
methods are illustrated through both simulation studies and real
applications.
This is an EXACT reproduction of a book published before 1923. This
IS NOT an OCR'd book with strange characters, introduced
typographical errors, and jumbled words. This book may have
occasional imperfections such as missing or blurred pages, poor
pictures, errant marks, etc. that were either part of the original
artifact, or were introduced by the scanning process. We believe
this work is culturally important, and despite the imperfections,
have elected to bring it back into print as part of our continuing
commitment to the preservation of printed works worldwide. We
appreciate your understanding of the imperfections in the
preservation process, and hope you enjoy this valuable book.
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