27 minute read
Artificial Intelligence / Fuzzy Logic
LEARNING (In 4 Volumes)
edited by Cheng Few Lee (Rutgers University, USA) & John C Lee (Center for PBBEF Research, USA)
Key Features
• A likely first attempt to combine the applications of econometrics, mathematics, statistics, and machine learning in finance research for academics and professionals • Contributions from well-known authors including Wayne Ferson,
Cheng Few Lee, Yangru Wu, Ivan
Brick, Darius Palia, Horng-Shing
Lu, Yong Shi, Son-Nan Chen,
T Robert Yu, Chunchi Wu and William H Greene
Readership: Researchers and professionals who are interested in financial econometrics, mathematics, statistics, and technology.
5056pp Sep 2020 978-981-120-238-4(Set) US$1950 £1715
Advanced Textbooks in Mathematics AN INTRODUCTION TO MACHINE LEARNING IN QUANTITATIVE FINANCE
by Hao Ni (University College London, UK), Xin Dong (Citadel Securities LLC, UK), Jinsong Zheng (Huatai Securities, China) & Guangxi Yu (SWS Research, China)
Key Features
• This book features financial applications, which distinguishes itself from other introductory textbooks in machine learning • Has a GitHub repository for all the codes and projects mentioned in the book
Readership: This textbook is suitable for MSc students or final year undergraduate students in financial mathematics, machine learning or computational finance. It would serve as a graduate textbook in introducing machine learning and its applications in quantitative finance. It may also be appropriate for those interested in pursuing a career in quantitative finance or for practitioners in the financial sector who wish to develop an in-depth understanding of machine learning and its applications to finance.
264pp Apr 2021 978-1-78634-964-4(pbk) US$48 £40 978-1-78634-936-1 US$88 £75
Singapore University of Social Sciences World Scientific Future Economy Series - Vol 2
THE EMERGING BUSINESS MODELS
by Chong Guan, Zhiying Jiang & Ding Ding (Singapore University of Social Sciences, Singapore)
Key Features
• The ability to identify and navigate the technologies and emerging business models disrupting the various industries • An opportunity to explore and incorporate key principles of transformative technology into new or existing business models Readership: Undergraduate and graduate students.
220pp Jun 2020 978-981-120-440-1(pbk) US$48 £40 978-981-120-392-3 US$88 £75
INTELLIGENT AUTOMATION: WELCOME TO THE WORLD OF HYPERAUTOMATION
Learn How to Harness Artificial Intelligence to Boost Business & Make Our World More Human
by Pascal Bornet, Ian Barkin (SYKES, USA) & Jochen Wirtz (National University of Singapore, Singapore)
“This book on Intelligent Automation is a mustread today for any organization executive — for profit or not. It describes in detail the advantages of human-and-robot interaction, emphasizing corporate, personal, and societal benefits. If you have not started to implement automation yet, this book can help be a catalyst for action. If you have already started your journey, effectively scaling automation programs will be the critical difference in winning in the Automation First era.” Daniel Dines, Co-Founder and CEO at UiPath Readership: Business owners, entrepreneurs, researchers and early adopters who are interested in the field of intelligent automation, artificial intelligence and machine learning.
432pp Jan 2021 978-981-123-559-7(pbk) US$24.99 £19 978-981-123-548-1 US$48 £40
BIOLOGICAL PATTERN DISCOVERY WITH R
Machine Learning Approaches
by Zheng RongYang (University of Exeter, UK)
Key Features
• Aims to integrate the theory of machine learning with R programming • Helps readers transfer their learning of machine learning theory to practical implementation • Focuses on individual biology pattern discoveries using machine learning approaches • Will be useful to those who have recently started their career in bioinformatics
Readership: Junior bioinformaticians and computational biologists, postgraduate students.
400pp 978-981-124-011-9 Dec 2021 US$118 £105
GENES, GERMS AND MEDICINE
The Life of Joshua Lederberg
by Jan Sapp (York University, Canada)
Genes, Germs and Medicine explores the development of modern biomedical science in the United States through the life of one of the Twentieth Century’s most influential scientists.
Readership: Molecular biologists, Microbiologists, Bioengineers, Historians of biology, Historians of medicine, Historians of Science, Microbial evolutionists, Evolutionary biologists.
424pp Mar 2021 978-981-123-598-6(pbk) US$38 £35 978-981-122-547-5 US$98 £85
ARTIFICIAL INTELLIGENCE PLATFORM FOR MOLECULAR TARGETED THERAPY
A Translational Science Approach
by Ariel Fernández (Former Hasselmann Professor of Bioengineering, Rice University, USA & CONICET, National Research Council, Argentina)
“These problems reach beyond the classical sequence-structure conundrum but are essential for structure-based drug development. This book addresses these problems and opens avenues of research and discovery for structural biologists who may find it very rewarding and of assistance in solving their problems.” Robert Huber, Nobel Laureate Readership: Primary market: Graduate students in Biomedical Engineering, MD/PhD or Computer Science focusing on interdisciplinary translational research. Pharmaceutical researchers seeking in-depth understanding of the physical principles at work in rational drug design. Practitioners in molecular targeted medicine and biotechnology seeking to enlarge their technological base through incorporation of AI. Secondary market: Academic physical chemists, bioinformaticians and biophysicists interested in incorporating AI to their research toolbox.
468pp 978-981-123-230-5 Apr 2021 US$148 £130
COMPUTING AND OPTIMIZATION FOR DC POWER SYSTEMS OF ELECTRIC TRANSPORT
by Dmytro Bosyi (Dnipro National University of Railway Transport, Ukraine), Oleh Sablin (Dnipro National University of Railway Transport, Ukraine) & Yevhen Kosariev (Dnipro National University of Railway Transport, Ukraine) Written at a time of rapid development of information technologies in various fields, this book serves as a kind of bridge for the introduction of artificial intelligence into the electric transport power supply systems. Readership: Senior students and postgraduate students of higher educational institutions, scientific employees of research institutes, specialists of design organizations.
220pp 978-1-78634-771-8 Mar 2020 US$98 £85
HUMAN ENACTMENT OF INTELLIGENT TECHNOLOGIES
Towards Mètis and Mindfulness
by W David Holford (University of Quebec at Montreal (UQAM), Canada)
This book demystifies what artificial intelligence is, examines its strength and limitations in comparison to what humans are capable of, and investigates the nature of human adaptive expertise across the concept of mètis. It also examines a particular family of mindsets that we as humans have adopted over the ages, namely epistemologies of representational knowledge.
Readership: Graduate, academics, and professionals in the fields of science, technology, and society, human-machine interaction, humancomputer interaction, cognitive robotics, and artificial intelligence.
250pp 978-981-123-727-0 Sep 2021 US$98 £85
AN INSIDE LOOK INTO CHINA’S AI DEVELOPMENT
CHINA AI REPORT 2020
Brought to you by SCMP Research
As an English-language media group with one of the largest on-the-ground technology reporting teams in China, the South China Morning Post has unmatched access and insights into the country’s leading and upcoming AI players.
Our report leverages on this first-hand access and insights to provide readers with useful intelligence and data presented in effective graphs and tables. Not only does it facilitate your research and better understanding of our findings, our in-depth case studies and analysis are also comprehensive for teaching references.
With the US and China accounting for 70 per cent of global AI Investment, it is crucial to take a deep dive into China AI’s development and deployment across industries, to have a better grasp of market development.
60pp Feb 2020 978-0-00-098913-0(ebook) US$800
Geometry of Statistical Manifolds and Divergences
by Hiroshi Matsuzoe (Nagoya Institute of Technology, Japan)
Key Features
• This book gives differential geometrical foundations of information geometry. • The contents of this book include basic applications of information geometry. For readers who are not an expert of statistics, these examples will help to understand the key essence of information geometry
Readership: Graduate students, researchers and professionals in Geometry.
350pp 978-981-4618-76-2 Aug 2022 US$130 £108
WHAT ARE TENSORS EXACTLY?
by Hongyu Guo (University of Houston-Victoria, USA)
The goal of this book is to elucidate the concepts in an intuitive way but without loss of rigor, to help students gain deeper understanding. As a result, they will not need to recite those definitions in a parrot-like manner any more. This volume answers common questions and corrects many misconceptions about tensors. A large number of illuminating illustrations helps the reader to understand the concepts more easily.
Readership: Researchers, professionals, academics, graduate students and undergraduate students in physics, AI, machine learning, and relativity and gravitation.
248pp 978-981-124-101-7 Jul 2021 US$58 £50
Series on Knots and Everything
MATHEMATICS OF HARMONY AS A NEW INTERDISCIPLINARY DIRECTION AND “GOLDEN” PARADIGM OF MODERN SCIENCE
Volume 1: The Golden Section, Fibonacci Numbers, Pascal Triangle, and Platonic Solids
by Alexey Stakhov (International Club of the Golden Section, Canada & Academy of Trinitarism, Russia)
Key Features:
• Development of the original historical and mathematical view on
Euclid’s “Elements”, based on the hypothesis of Proclus (411 – 485) • Generalization of Fibonacci numbers and golden section, following from the diagonal sums of Pascal triangle (mathematical discovery of the outstanding American mathematician George Polya) • A new view on the role of the Fibonacci numbers theory in modern mathematics
Readership: High school, college and university students and teachers, professionals, scientists and investors interested in history of mathematics, Fibonacci numbers, golden section and their generalization.
248pp 978-981-120-710-5 May 2020 US$88 £75
BASIC PROBABILITY
What Every Math Student Should Know
(2nd Edition)
by HenkTijms (Vrije University, The Netherlands)
Reviews of the First Edition:
“What makes this book unique among books of similar size and scope is that when the author decided to include something in the book, he has treated it in a way similar to the common practice in textbooks, with very detailed and reader-friendly explanations, fully worked-out examples, and even numerous exercises ... There are no prerequisites beyond second-semester calculus and the book can be used for selfstudy as well as in the classroom.” CHOICE Readership: Undergraduate students in fields such as mathematics, statistics and data science, engineering, computer science and business analytics. Graduate students in natural and social sciences. Students taking a first course in probability, or a course on probability for statistics and data science. High school math teachers and STEM students. Students in natural and social sciences, economics and finance.
180pp ug 2021 978-981-123-851-2(pbk) US$34 £30 978-981-123-749-2 US$58 £50
DEEP LEARNING FOR PHYSICS RESEARCH
by MartinErdmann (RWTH Aachen University, Germany), Jonas Glombitza (RWTH Aachen University, Germany), Gregor Kasieczka (University of Hamburg, Germany) & Uwe Klemradt (RWTH Aachen University, Germany)
Key Features
• This is the first textbook on deep learning technology addressing physicists • The book is based on a lecture series with application-oriented design • Solutions to neural network exercises and data are available at World
Scientific Readership: Physicists worldwide who are looking for a practical introduction to the technology of deep learning, as it provides comprehensive course material for physics students (2nd year and above) to get started in a subfield of artificial intelligence.
340pp 978-981-123-745-4
ARTIFICIAL INTELLIGENCE FOR HIGH ENERGY PHYSICS
edited by PaoloCalafiura (Lawrence Berkeley National Laboratory, USA), David Rousseau (Laboratoire de Physique des 2 Infinis Irène Joliot-Curie, France) & Kazuhiro Terao (SLAC National Accelerator Laboratory, USA)
Key Features
• It provides the reader with state-of-the-art tools to address classic HEP research problems and with the foundations to develop methods to solve new ones • This book bridges the gap between introductory general-purpose machine learning texts and cutting-edge research papers in AI applied to HEP. This is the book researchers always want to have handy when a new student or researcher joins their groups
Readership: Graduate students and physicists interested in AI/ML applications to HEP; data scientists and ML researchers interested in “big science” data analysis and simulation.
720pp 978-981-123-402-6 Dec 2021 US$188 £165
APPLIED SOFTWARE DEVELOPMENT WITH PYTHON & MACHINE LEARNING BY WEARABLE & WIRELESS SYSTEMS FOR MOVEMENT DISORDER TREATMENT VIA DEEP BRAIN STIMULATION
by Robert LeMoyne (Northern Arizona University, USA) & Timothy Mastroianni
Key Features
• This book enables the reader to conduct unique and substantive research, only bounded by their own creativity. The book covers the application of wearable and wireless inertial systems, such as a smartphone, for the quantification of a highly prevalent movement disorder (Essential tremor) • Central to the application of machine learning, which is thoroughly discussed from an applied perspective, is the presented software development process using Python for post-processing the acquired inertial signal data
Readership: Students and Professionals in Machine Learning and AI.
250pp 978-981-123-595-5 Aug 2021 US$88 £75
CLUSTERING
Theoretical and Practical Aspects
by Dan A Simovici (University of Massachusetts Boston, USA)
This unique compendium gives an updated presentation of clustering, one of the most challenging tasks in machine learning. The book provides a unitary presentation of classical and contemporary algorithms ranging from partitional and hierarchical clustering up to density-based clustering, clustering of categorical data, and spectral clustering.
Readership: Researchers, professionals, academics and graduate students in machine learning, data mining and artificial intelligence.
From Beginning to Date
by Zi-Xing Cai (Central South University, China & Hunan ZIXING AI Academy, China), Lijue Liu (Central South University, China & Hunan ZIXING AI Academy, China), Baifan Chen (Central South University, China & Hunan ZIXING AI Academy, China) & YongWang (Central South University, China)
This book has obvious innovations in the organization of content. Based on the core technology of artificial intelligence, the book is divided into three parts, namely, knowledge-based artificial intelligence, data-based artificial intelligence, and the main application areas of artificial intelligence
Readership: Readerships are majorly in the discipline/profession of artificial intelligence, intelligent S&T, computer science and engineering, automatic control, electronic engineering, management and decision system engineering, mechatronic engineering and robotics, etc.
576pp 978-981-122-371-6 Jun 2021 US$158 £140
MACHINE LEARNING
Concepts, Tools and Data Visualization
by Minsoo Kang (Eulji University, South Korea) & Eunsoo Choi (All4Land Inc., South Korea)
This set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important concepts in the field of machine learning. It consists of three parts. The first is an overview of the history of artificial intelligence, machine learning, and data science, and also includes case studies of well-known AI systems. The second is a step-by-step introduction to Azure Machine Learning, with examples provided. The third is an explanation of the techniques and methods used in data visualization with R, which can be used to communicate the results collected by the AI systems when they are analyzed statistically. Practice questions are provided throughout the book.
Readership: Students of artificial intelligence and engineers working in artificial intelligence.
296pp Mar 2021 978-981-122-936-7(pbk) US$48 £40 978-981-122-814-8 US$108 £95
BRAIN VS COMPUTER
The Challenge of the Century is Now Launched
(2nd Edition)
by Jean-Pierre Fillard
Review of the First Edition:
“General readers (especially) and all those involved in computing will benefit from considering the profound questions that are raised in this work.” CHOICE connect Readership: General public who are interested in the competition between brain and computer, and artificial intelligence.
324pp Nov 2020 978-981-122-626-7(pbk) US$48 £40 978-981-122-500-0 US$98 £85
COGNITIVE SATELLITE SYSTEM
by Jianjun Zhang (China Academy of Space Technology, China) & Jing Li (Beijing Institute of Technology, China)
Key Features
• For the first time, the book applies cognitive concept to the design of satellite systems • This book introduces cognitive radio theory into satellite communication systems, and realizes the concept of dynamic spectrum access of satellite cognitive wireless networks, to overcome current shortage of spectrum resources available in satellite communication systems
Readership: This is an advanced text that applies cognitive systems to satellite technologies. It will be useful to scientists and researchers working on spacecraft technology and intelligent decision making.
328pp 978-981-121-434-9 Sep 2020 US$128 £115
DEEP LEARNING IN BIOLOGY AND MEDICINE
edited by Davide Bacciu (University of Pisa, Italy), Paulo J G Lisboa (Liverpool John Moores University, UK) & Alfredo Vellido (Polytechnic University of Catalonia, Spain)
Key Features
• The first to bring deep learning techniques to the life science communities, whereas other books are focused on bringing life science knowledge to the deep learning community • An overview of consolidated approaches and methods as well as an up-to-date overview of the state-of-the-art methodologies and applications of deep learning in biology and medicine. As such, the book is also a useful guide to help navigate the literature, providing a reference for both practitioners and scientists • The book also includes several useful references to shared resources, i.e. datasets, code, networks, etc.
Readership: Researchers and practitioners in the fields of machine learning, data science, artificial intelligence, statistics, bioinformatics, computational biology, biology, medicine and chemistry.
268pp 978-1-80061-093-4 Oct 2021 US$98 £85
WSPC Book Series in Unconventional Computing
HANDBOOK OF UNCONVENTIONAL COMPUTING
(In 2 Volumes) Volume 1: Theory Volume 2: Implementations
edited by Andrew Adamatzky (University of West of England, Bristol, UK) The book is a professional introduction to alternative computing — the interdisciplinary science aimed to exploit principles of information processing in and functional properties of physical, chemical and living systems to develop efficient algorithms, design optimal architectures and manufacture working prototypes of future and emergent computing devices Readership: The book is inter-disciplinary, it appeals to computer scientists, engineers, mathematicians, physicists, chemists, philosophers, logicians. May also be ideal supplementary reading for courses on theory of computation, future and emergent technologies, complex systems, mathematical machines, automata theory and applications, non-linear systems, complexity, unconventional computing.
A Realistic Future?
by Jean-Pierre Fillard
Key Features
• It explores the futuristic topic of a successful co-existence of man and machine, not as separate entitles, but integrated • It will be a welcome addition to the handful of titles on the subject of transhumanism
Readership: This book is intended for the general public as an introduction to a sub-field of Artificial Intelligence.
204pp May 2020 978-981-121-210-9(pbk) US$38 £35 978-981-121-138-6 US$78 £70
ARTIFICIAL INTELLIGENCE AND EMERGING TECHNOLOGIES IN INTERNATIONAL RELATIONS
by Bhaso Ndzendze (University of Johannesburg, South Africa) & Tshilidzi Marwala (University of Johannesburg, South Africa)
Key Features
• The book characterises the early effects of new technologies in international relations and evaluates their theoretical and policy implications • The book is comprehensive in its evaluation of the origins and lifecycles of technologies and the advantages they generate for countries which have and do not have them, as well as the global effects of such technological inequalities
Readership: Researchers and postgraduate students of International Relations, Political Science as well as Computer Science and Information Engineering. These are in the English-speaking and technologically advanced markets such as the UK, the US, Canada, Australia, Israel, Singapore, as well as the growing AI and technology markets and scholarships in South Africa, Kenya, Rwanda, Nigeria and Ethiopia.
192pp 978-981-123-454-5 Jun 2021 US$78 £70
Volume II: Fundamentals of Optimization Theory with Applications to Machine Learning
by Jean Gallier (University of Pennsylvania, USA) & Jocelyn Quaintance (University of Pennsylvania, USA)
Key Features
• Combines the most crucial aspects of linear and nonlinear optimization under one volume • The reader friendly writing style which presents difficult concepts in a “down to earth” example driven manner
Readership: Students going for advanced undergraduate applied math classes; master levels classes in engineering optimization, machine learning, and applied mathematics; and doctoral seminar classes in machine learning and engineering optimization.
896pp 978-981-121-656-5 May 2020 US$198 £175
Volume I: Linear Algebra for Computer Vision, Robotics, and Machine Learning
by Jean Gallier (University of Pennsylvania, USA) & Jocelyn Quaintance (University of Pennsylvania, USA)
Key Features
• This book fills a gap in the market in that it is a mathematically rigorous book which provides topical applications for the fields of machine learning, computer vision, and robotics • This book covers, in more depth than usual, duality (Chapter 9), vector and matrix norms (Chapter 7), and the spectral theorems (Chapter 15)
Readership: Undergraduate and graduate students interested in mathematical fundamentals of linear algebra in computer vision, machine learning, robotics, applied mathematics, and electrical engineering.
824pp Feb 2020 978-981-120-771-6(pbk) US$98 £85 978-981-120-639-9 US$198 £175
STATISTICAL MACHINE LEARNING WITH APPLICATIONS IN FINANCE
by Gordon Ritter (Columbia University, USA & New York University, USA & Baruch College, USA)
This unique compendium develops a general approach to building models of economic and financial processes, with a focus on statistical learning techniques that scale to large data sets. It introduces the key elements of a parametric statistical model: likelihood, prior, and posterior, and show how to use them to make predictions.
Readership: Professionals, academics, researchers, and graduate students in artificial intelligence/machine learning, neural networks, pattern recognition, and machine perception/computer vision.
480pp 978-981-123-233-6 Jan 2022 US$128 £115
ARTIFICIAL INTELLIGENCE/ HUMAN INTELLIGENCE
An Indissoluble Nexus
by Richard J Wallace (University College Cork, Ireland)
Key Features
• Artificial intelligence looked at from a novel viewpoint that machine intelligence is an artificial aid to human intelligence, and the two co-exist in improving to deliver a better solution • Clarification of “superintelligence” and similar ideas
Readership: Anyone from the general public with an interest in AI.
368pp Mar 2021 978-981-123-308-1(pbk) US$38 £35 978-981-123-287-9 US$78 £70
Textbook: Request Inspection Copy at sales@wspc.com
GENERALIZATION WITH DEEP LEARNING
For Improvement on Sensing Capability
edited by Zhenghua Chen, Min Wu & Xiaoli Li (Institute for Infocomm Research, Singapore)
Key Features
• To showcase Deep Learning applications in the area of sensing, including medical image processing, remote sensing, human activity recognition, etc. • To feature Deep Learning as a technology capable of learning inductively to create concepts • With this ability to learn from examples, and generalize into concepts, this edited volume will attempt to narrow the gap between human and machine and pave the way the arrival of thinking machine
Readership: This volume is aimed at fellow researchers in the field of deep learning in AI, with the aim of showcasing various applications in the area of sensing.
324pp 978-981-121-883-5 Apr 2021 US$108 £95
GRANULAR VIDEO COMPUTING
with Rough Sets, Deep Learning and in IoT
by Debarati B Chakraborty (Indian Institute of Technology Jodhpur, India) & Sankar K Pal (Indian Statistical Institute Kolkata, India)
Key Features
• Linking the concept of granular computing using deep learning and the Internet of
Things to object tracking for video analysis • Is structured according to the major challenges of video processing (e.g., tracking, occlusion handling, reliability measure, scene recognition, and real-time event prediction in IoT) while defining new variations of rough sets and granular computing developed depending on the type of problems
Readership: Graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology.
256pp 978-981-122-711-0 Mar 2021 US$88 £75
WHAT IS ARTIFICIAL INTELLIGENCE?
A Conversation between an AI Engineer and a Humanities Researcher
by Suman Gupta (The Open University, UK) & Peter H Tu (General Electric Research, USA)
“A light-hearted, but engaging conversation about one of the key technologies of our age.
I recommend this book to anyone interested in the broader issues around Artificial Intelligence.” Richard Hartley, Australian National University, Australia
Readership: General informed readers. Readers with knowledge of AI and its underpinning principles will be interested. In particular, those with a disciplinary background in computing and technological development, policy studies, current affairs, philosophy and discourse analysis. Appropriate for undergraduate students and upwards, or those whose interest is more conceptual than the general user of technology. Intelligent Information Systems - Vol 6
RECOMMENDER SYSTEMS
Advanced Developments
by Jie Lu, Qian Zhang & Guangquan Zhang (University of Technology Sydney, Australia) The comprehensive volume provides readers with a timely snapshot of how new recommendation methods and algorithms can overcome challenging issues. Furthermore, the monograph systematically presents three dimensions of recommender systems — basic recommender system concepts, advanced recommender system methods, and real-world recommender system applications. Readership: Professionals, academics, researchers, and graduate students in artificial intellgence/machine learning and databases.
352pp 978-981-122-462-1 Aug 2020 US$138 £120
East China Normal University Scientific Reports - Vol 11
Data, Community and Influence
by Kun Yue, Jin Li, Hao Wu, Weiyi Liu & Zidu Yin (Yunnan University, China) This unique compendium focuses on the acquisition and analysis of social media data. The approaches concern both the dataintensive characteristics and graphical structures of social media. The book addresses the critical problems in social media analysis, which representatively cover its lifecycle. Readership: Professionals, researchers, academics and graduate students in AI and databases.
292pp 978-981-120-737-2 Mar 2020 US$118 £105
World Scientific Series on Emerging Technologies: Avram Bar-Cohen Memorial Series - Vol 1
HANDBOOK ON BIG DATA AND MACHINE LEARNING IN THE PHYSICAL SCIENCES
(In 2 Volumes) Volume 1: Big Data Methods in Experimental Materials Discovery Volume 2: Advanced Analysis Solutions for Leading Experimental Techniques
edited by Surya Kalidindi (GaTech, USA), Sergei V Kalinin (Oak Ridge National Laboratory, USA), Turab Lookman (Los Alamos National Laboratory, USA), Kerstin Kleese van Dam (Brookhaven National Laboratory, USA), Kevin G Yager (Brookhaven National Laboratory, USA), Stuart I Campbell (Brookhaven National Laboratory, USA), Richard Farnsworth (Brookhaven National Laboratory, USA) & Maartje van Dam (Brookhaven National Laboratory, USA) Editors-in-chief: Sergei V Kalinin (Oak Ridge National Laboratory, USA) & Ian Foster (Argonne National Laboratory, USA & University of Chicago, USA) This compendium provides a comprehensive collection of the emergent applications of big data, machine learning, and artificial intelligence technologies to present day physical sciences ranging from materials theory and imaging to predictive synthesis and automated research. This area of research is among the most rapidly developing in the last several years in areas spanning materials science, chemistry, and condensed matter physics. Readership: Professionals, researchers, academics, and graduate students in artificial intelligence, robotics and machine learning.
1000pp May 2020 978-981-120-444-9(Set) US$980 £860
DECOMPOSITIONBASED EVOLUTIONARY OPTIMIZATION IN COMPLEX ENVIRONMENTS
by Juan Li (Beijing Institute of Technology, China), Bin Xin (Beijing Institute of Technology, China) & Jie Chen (Beijing Institute of Technology, China)
Key Features
• Algorithm design • Application of multi-objective uncertain optimization approaches
Readership: Researchers and professionals in computer science that specialise or deal with multi-objective optimization and uncertain optimization in decision making, system designing, and scheduling.
248pp 978-981-121-898-9 Aug 2020 US$98 £85
TOWARD SUSTAINABLE AND ECONOMIC SMART MOBILITY
Shaping the Future of Smart Cities
edited by Max Eiza (University of Central Lancashire, UK), Yue Cao (Lancaster University, UK) & Lexi Xu (China Unicom, China & Beijing University of Posts and Telecommunications, China)
Key Features
• This book is brought to you by authors from different backgrounds in academia and industry from around the world • The materials have been carefully selected to reflect the latest developments in the field with many novel contributions from the contributors
Readership: Professionals and researchers in the areas of Smart Mobility (e.g., autonomous valet parking, passenger trajectory data, smart traffic control systems), general public interested in technological advances.
212pp 978-1-78634-785-5 Jul 2020 US$88 £75
edited by Meir Kalech (Ben-Gurion University of the Negev, Israel), Rui Abreu (University of Porto, Portugal) & Mark Last (Ben-Gurion University of the Negev, Israel)
This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).
Readership: Researchers, academics, professionals and graduate students in artificial intelligence/machine learning and software engineering.
456pp 978-981-123-991-5 Jul 2021 US$158 £140
PYTHON, DATA SCIENCE AND MACHINE LEARNING
From Scratch to Productivity
by Paul Alexander Bilokon (Thalesians Ltd, UK)
Key Features
• Covers Data Science and Machine Learning, the most topical technical subjects of our day • No formal prerequisites, includes an overview of Python, both foundations and advanced features • Covers the mathematical foundations of Data Science and Machine
Learning, teaches through case studies built on real dataset and includes numerous solved exercises
Readership: Aspiring Data Scientists and Machine Learning (ML) experts — undergraduate, graduate, and independent. Also applicable to Software developers, engineers, and others working in technical professions interested in learning about Data Science and Machine Learning; and Managers working in financial, technological, and medical organisations, interested in learning about Data Science and Machine Learning.
300pp 978-981-121-572-8 Jun 2022 US$98 £85
PRINCIPLES OF QUANTUM ARTIFICIAL INTELLIGENCE
Quantum Problem Solving and Machine Learning
(2nd Edition)
by Andreas Wichert (Instituto Superior Técnico - Universidade de Lisboa, Portugal & INESC-ID, Portugal)
This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence.
Readership: Professionals, researchers, academics, and graduate students in databases, artificial intelligence, pattern recognition and neural networks.
496pp 978-981-122-430-0 Aug 2020 US$168 £150
TO HALT, OR NOT TO HALT. THAT IS THE QUESTION
by Cristian S Calude (University of Auckland, New Zealand)
Written in an informal and thought-provoking language, supported with suggestive illustrations and applications and almost free of arcane mathematics (formal arguments are relegated to a special part dedicated to the mathematically-oriented reader), the book will stimulate the curiosity of the reader interested in the consequences of the limits of computing and in various attempts to cope with them.
Readership: Undergraduate and graduate students, researchers and practitioners in the fields of computer science, mathematics, logic, philosophy, physics, and a large category of educated readers.
250pp 978-981-123-227-5 Jan 2022 US$98 £85
FIND THESE BOOKS VALUABLE TO YOUR COMMUNITY? RECOMMEND THEM TO YOUR LIBRARIAN.
Empowering Digital Economy
by Yang Yan (Zhongguancun BigData Industry Alliance, China & Zhongguancun Digital Media Industry Alliance, China & Terminus Technologies Group, China), Bin Wang (Zhongguancun BigData Industry Alliance, China & Zhongguancun Digital Media Industry Alliance, China & Terminus Technologies Group, China) & Jun Zou (Zhongguancun BigData Industry Alliance, China & Zhongguancun Digital Media Industry Alliance, China & Terminus Technologies Group, China)
The volume will be a useful reference guide for relevant personnel in state ministries and commissions, state-owned enterprises, big data, AI, as well as teachers, researchers and students in higher education institutions.
Readership: Professionals, academics, researchers, and graduate students in artifical intelligence, digital security, and databases.
150pp 978-981-123-650-1 Jul 2021 US$48 £40
Series on Deep Learning Neural Networks - Vol 1 ARTIFICIAL NEURAL NETWORKS
Methods and Applications in Fractional Order Systems
by Susmita Mall & Snehashish Chakraverty (National Institute of Technology Rourkela, India)
Key Feature
• The present book will make a new vista for the readers which may give an intelligent way to the fractional order systems with the help of ANNs. Our main aim here is to handle the FDEs governing the fractional order models using the recently developed machine intelligence method viz ANNS
Readership: This book will be an essential source for students, scholars, practitioners, researchers and academicians in the assorted fields of engineering and sciences interested to model physical problems with ease through the use of ANN.
250pp 978-981-121-880-4 May 2022 US$98 £85
SELF-ORGANISING MULTI-AGENT SYSTEMS
Algorithmic Foundations of CyberAnarcho-Socialism
by Jeremy Pitt (Imperial College London, UK)
Key Features
• There is no other book which so comprehensively tackles such a range of important engineering and social issues which are so pertinent to the study, design and implementation of socio-technical systems in the Digital Society • The approach is highly inter-disciplinary and far-reaching in scope. It contains knowledge and insight which is important for engineers to understand. It analyses deep theoretical issue but also demonstrates by code
Readership: Advanced Undergraduates, Master’s Students and PhD Students in Computer Science and Artificial Intelligence subjects. Supports an entire course on self-organising multi-agent systems.
346pp 978-1-80061-042-2 Sep 2021 US$128 £115
MACHINE LEARNING — A JOURNEY TO DEEP LEARNING
with Exercises and Answers
by Andreas Wichert (Instituto Superior Técnico — Universidade de Lisboa, Portugal & INESC-ID, Portugal) & Luis Sa-Couto (Instituto Superior Técnico — Universidade de Lisboa, Portugal & INESC-ID, Portugal)
The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.
Readership: Professionals, academics, researchers, and graduate students in artificial intelligence/machine learning, neural networks, pattern recognition, and machine perception/computer vision.
640pp 978-981-123-405-7 Feb 2021 US$168 £150
Representations, Algorithms and Applications
by Xiang Zhang (Harvard University, USA & University of New South Wales, Australia) & Lina Yao (University of New South Wales, Australia)
Deep Learning for EEG-based Brain-Computer Interfaces is an exciting book that describes how emerging deep learning improves the future development of Brain-Computer Interfaces (BCI) in terms of representations, algorithms, and applications. BCI bridges humanity’s neural world and the physical world by decoding an individuals’ brain signals into commands recognizable by computer devices.
Readership: Advanced undergraduate and graduate students, researchers and practitioners in the fields of computer science, data mining, artificial intelligence, and neuroscience. Will also be of interest to industry or companies invested in combining brain signals with real world applications including user authentication, neurological diagnosis, autonomous cars, smart homes, IoT, etc.
340pp 978-1-78634-958-3 Aug 2021 US$128 £115
ARTIFICIAL BRAINS
An Evolved Neural Net Module Approach
by Hugo de Garis (Xiamen University, China)
Key Features
• The first artificial brain textbook in the world • A step-by-step textbook, explaining how any computer research lab can also build artificial brains by following the techniques explained in the text • Written in clear fluid prose by an experienced and previously published author
Readership: Undergraduate and graduate students in the field of artificial brain, artificial intelligence and robotics.
