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Robotics is an ever-expanding field and intelligent planning
continues to play a major role. Given that the intention of mobile
robots is to carry out tasks independent from human aid, robot
intelligence is needed to make and plan out decisions based on
various sensors. Planning is the fundamental activity that
implements this intelligence into the mobile robots to complete
such tasks. Understanding problems, challenges, and solutions to
path planning and how it fits in is important to the realm of
robotics. Intelligent Planning for Mobile Robotics: Algorithmic
Approaches presents content coverage on the basics of artificial
intelligence, search problems, and soft computing approaches. This
collection of research provides insight on both robotics and basic
algorithms and could serve as a reference book for courses related
to robotics, special topics in AI, planning, applied soft
computing, applied AI, and applied evolutionary computing. It is an
ideal choice for research students, scholars, and professors alike.
Soft Computing today is a very vast field whose extent is beyond
measure. The boundaries of this magnificent field are spreading at
an enormous rate making it possible to build computationally
intelligent systems that can do virtually anything, even after
considering the hostile practical limitations. Soft Computing,
mainly comprising of Artificial Neural Networks, Evolutionary
Computation, and Fuzzy Logic may itself be insufficient to cater to
the needs of various kinds of complex problems. In such a scenario,
we need to carry out amalgamation of same or different computing
approaches, along with heuristics, to make fabulous systems for
problem solving. There is further an attempt to make these
computing systems as adaptable as possible, where the value of any
parameter is set and continuously modified by the system itself.
This book first presents the basic computing techniques, draws
special attention towards their advantages and disadvantages, and
then motivates their fusion, in a manner to maximize the advantages
and minimize the disadvantages. Conceptualization is a key element
of the book, where emphasis is on visualizing the dynamics going
inside the technique of use, and hence noting the shortcomings. A
detailed description of different varieties of hybrid and adaptive
computing systems is given, paying special attention towards
conceptualization and motivation. Different evolutionary techniques
are discussed that hold potential for generation of fairly complex
systems. The complete book is supported by the application of these
techniques to biometrics. This not only enables better
understanding of the techniques with the added application base, it
also opens new dimensions of possibilities how multiple biometric
modalities can be fused together to make effective and scalable
systems.
Bridging the disciplines of engineering and medicine, ""Biomedical
Engineering and Information Systems: Technologies, Tools and
Applications"", informs researchers, clinicians, and practitioners
of the latest developments in diagnostic tools, decision support
systems, and intelligent devices that impact and redefine research
in and delivery of medical services.
This book includes introduction of several algorithms which are
exclusively for graph based problems, namely combinatorial
optimization problems, path formation problems, etc. Each chapter
includes the introduction of the basic traditional nature inspired
algorithm and discussion of the modified version for discrete
algorithms including problems pertaining to discussed algorithms.
The book presents high quality research papers presented at
International Conference on Computational Intelligence (ICCI 2020)
held at Indian Institute of Information Technology, Pune, India
during 12-13 December, 2020. The topics covered are artificial
intelligence, neural network, deep learning techniques, fuzzy
theory and systems, rough sets, self-organizing maps, machine
learning, chaotic systems, multi-agent systems, computational
optimization ensemble classifiers, reinforcement learning, decision
trees, support vector machines, hybrid learning, statistical
learning. metaheuristics algorithms: evolutionary and swarm-based
algorithms like genetic algorithms, genetic programming,
differential evolution, particle swarm optimization, whale
optimization, spider monkey optimization, firefly algorithm,
memetic algorithms. And also machine vision, Internet of Things,
image processing, image segmentation, data clustering, sentiment
analysis, big data, computer networks, signal processing, supply
chain management, web and text mining, distributed systems,
bioinformatics, embedded systems, expert system, forecasting,
pattern recognition, planning and scheduling, time series analysis,
human-computer interaction, web mining, natural language
processing, multimedia systems, and quantum computing.
This book includes introduction of several algorithms which are
exclusively for graph based problems, namely combinatorial
optimization problems, path formation problems, etc. Each chapter
includes the introduction of the basic traditional nature inspired
algorithm and discussion of the modified version for discrete
algorithms including problems pertaining to discussed algorithms.
Soft Computing today is a very vast field whose extent is beyond
measure. The boundaries of this magnificent field are spreading at
an enormous rate making it possible to build computationally
intelligent systems that can do virtually anything, even after
considering the hostile practical limitations. Soft Computing,
mainly comprising of Artificial Neural Networks, Evolutionary
Computation, and Fuzzy Logic may itself be insufficient to cater to
the needs of various kinds of complex problems. In such a scenario,
we need to carry out amalgamation of same or different computing
approaches, along with heuristics, to make fabulous systems for
problem solving. There is further an attempt to make these
computing systems as adaptable as possible, where the value of any
parameter is set and continuously modified by the system itself.
This book first presents the basic computing techniques, draws
special attention towards their advantages and disadvantages, and
then motivates their fusion, in a manner to maximize the advantages
and minimize the disadvantages. Conceptualization is a key element
of the book, where emphasis is on visualizing the dynamics going
inside the technique of use, and hence noting the shortcomings. A
detailed description of different varieties of hybrid and adaptive
computing systems is given, paying special attention towards
conceptualization and motivation. Different evolutionary techniques
are discussed that hold potential for generation of fairly complex
systems. The complete book is supported by the application of these
techniques to biometrics. This not only enables better
understanding of the techniques with the added application base, it
also opens new dimensions of possibilities how multiple biometric
modalities can be fused together to make effective and scalable
systems.
Rapid advancements in the application of soft computing tools and
techniques have proven valuable in the development of highly
scalable systems and resulted in brilliant applications, including
those in biometric identification, interactive voice response
systems, and data mining. Although many resources on the subject
adequately cover the theoretic concepts, few provide clear insight
into practical application. Filling this need, Real Life
Applications of Soft Computing explains such applications,
including the underlying technology and its implementation. While
these systems initially seem complex, the authors clearly
demonstrate how they can be modeled, designed, and implemented.
Written in a manner that makes it accessible to novices, the book
begins by covering the theoretical foundations of soft computing.
It supplies a concise explanation of various models, principles,
algorithms, tools, and techniques, including artificial neural
networks, fuzzy systems, evolutionary algorithms, and hybrid
algorithms. Supplying in-depth exposure to real life systems, the
text provides: Multi-dimensional coverage supported by references,
figures, and tables Warnings about common pitfalls in the
implementation process, as well as detailed examinations of
possible solutions A timely account of developments in various
areas of application Solved examples and exercises in each chapter
Detailing a wide range of contemporary applications, the text
includes coverage of those in biometric systems, including
physiological and behavioral biometrics. It also examines
applications in legal threat assessment, robotic path planning, and
navigation control. The authors consider fusion methods in
biometrics and bioinformatics and also provide effective disease
identification techniques. Co
The book presents high quality research papers presented at
International Conference on Computational Intelligence (ICCI 2020)
held at Indian Institute of Information Technology, Pune, India
during 12-13 December, 2020. The topics covered are artificial
intelligence, neural network, deep learning techniques, fuzzy
theory and systems, rough sets, self-organizing maps, machine
learning, chaotic systems, multi-agent systems, computational
optimization ensemble classifiers, reinforcement learning, decision
trees, support vector machines, hybrid learning, statistical
learning. metaheuristics algorithms: evolutionary and swarm-based
algorithms like genetic algorithms, genetic programming,
differential evolution, particle swarm optimization, whale
optimization, spider monkey optimization, firefly algorithm,
memetic algorithms. And also machine vision, Internet of Things,
image processing, image segmentation, data clustering, sentiment
analysis, big data, computer networks, signal processing, supply
chain management, web and text mining, distributed systems,
bioinformatics, embedded systems, expert system, forecasting,
pattern recognition, planning and scheduling, time series analysis,
human-computer interaction, web mining, natural language
processing, multimedia systems, and quantum computing.
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