Cognitive architectures represent an umbrella term to describe ways in which the flow of thought can be engineered towards cerebral and behavioral outcomes. Cognitive Architectures are meant to provide top-down guidance, a knowledge base, interactive heuristics and concrete or fuzzy policies for which the virtual character can utilize for intelligent interaction with his/her/its situated virtual environment. Integrating Cognitive Architectures into Virtual Character Design presents emerging research on virtual character artificial intelligence systems and procedures and the integration of cognitive architectures. Emphasizing innovative methodologies for intelligent virtual character integration and design, this publication is an ideal reference source for graduate-level students, researchers, and professionals in the fields of artificial intelligence, gaming, and computer science.

This is the fifth volume of a sub series on Road Vehicle Automation published within the Lecture Notes in Mobility. Like in previous editions, scholars, engineers and analysts from all around the world have contributed chapters covering human factors, ethical, legal, energy and technology aspects related to automated vehicles, as well as transportation infrastructure and public planning. The book is based on the Automated Vehicles Symposium which was hosted by the Transportation Research Board (TRB) and the Association for Unmanned Vehicle Systems International (AUVSI) in San Francisco, California (USA) in July 2017.

This book discusses the use of efficient metaheuristic algorithms to solve diverse power system problems, providing an overview of the various aspects of metaheuristic methods to enable readers to gain a comprehensive understanding of the field and of conducting studies on specific metaheuristic algorithms related to power-system applications. By bridging the gap between recent metaheuristic techniques and novel power system methods that benefit from the convenience of metaheuristic methods, it offers power system practitioners who are not metaheuristic computation researchers insights into the techniques, which go beyond simple theoretical tools and have been adapted to solve important problems that commonly arise. On the other hand, members of the metaheuristic computation community learn how power engineering problems can be translated into optimization tasks, and it is also of interest to engineers and application developers. Further, since each chapter can be read independently, the relevant information can be quickly found. Power systems is a multidisciplinary field that addresses the multiple approaches used for design and analysis in areas ranging from signal processing, and electronics to computational intelligence, including the current trend of metaheuristic computation.

This book explores Ambient Intelligence as applied to the classroom, while especially focusing on the use of personalized education to optimize the learning process. In the years to come, the dynamics of learning spaces in higher education will need to evolve and adapt to a constantly changing digital society, as learners and educators alike attune their learning competences and teaching skills. Ambient Intelligence is another way that Artificial Intelligence is being utilized in a plethora of real-world situations, amongst which classrooms and other learning spaces offer fitting settings and ideal environments for employing this assistive technology. The book presents a complete and novel approach to deploying the Ambient Intelligent Classroom, based on three interrelated aspects - the Social, the Technological and the Educational, - in order to provide a rich three-dimensional learning environment. This book is intended for education technologists and AI researchers, as well as for those tech-savvy readers interested in applying technology to the future of learning spaces. Educators in particular will find valuable insights and guidelines on how to shape the evolution of their own classroom.

Accessible to all readers, including students of secondary school and amateur technology enthusiasts, Robotics, Mechatronics, and Artificial Intelligence simplifies the process of finding basic circuits to perform simple tasks, such as how to control a DC or step motor, and provides instruction on creating moving robotic parts, such as an "eye" or an "ear." Though many companies offer kits for project construction, most experimenters want to design and build their own robots and other creatures specific to their needs and goals. With this new book by Newton Braga, hobbyists and experimenters around the world will be able to decide what skills they want to feature in a project and then choose the right "building blocks" to create the ideal results.
In the past few years the technology of robotics, mechatronics, and artificial intelligence has exploded, leaving many people with the desire but not the means to build their own projects. The author's fascination with and expertise in the exciting field of robotics is demonstrated by the range of simple to complex project blocks he provides, which are designed to benefit both novice and experienced robotics enthusiasts. The common components and technology featured in the project blocks are especially beneficial to readers who need practical solutions that can be implemented easily by their own hands, without incorporating expensive, complicated technology.
Accessible to technicians and hobbyists with many levels of experience, and written to provide inexpensive and creative fun with robotics
Appeals to all sorts of technology enthusiasts, including those involved with electronics, computers, home automation, mechanics, and other areas.

As global communities are attempting to transform into more efficient and technologically-advanced metropolises, artificial intelligence (AI) has taken a firm grasp on various professional fields. Technology used in these industries is transforming by introducing intelligent techniques including machine learning, cognitive computing, and computer vision. This has raised significant attention among researchers and practitioners on the specific impact that these smart technologies have and what challenges remain. Applications of Artificial Intelligence for Smart Technology is a pivotal reference source that provides vital research on the implementation of advanced technological techniques in professional industries through the use of AI. While highlighting topics such as pattern recognition, computational imaging, and machine learning, this publication explores challenges that various fields currently face when applying these technologies and examines the future uses of AI. This book is ideally designed for researchers, developers, managers, academicians, analysts, students, and practitioners seeking current research on the involvement of AI in professional practices.

This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 9th International Conference on Complex Networks (CompleNet) in Boston, MA, March, 2018. With roots in physical, information and social science, the study of complex networks provides a formal set of mathematical methods, computational tools and theories to describe, prescribe and predict dynamics and behaviors of complex systems. Despite their diversity, whether the systems are made up of physical, technological, informational, or social networks, they share many common organizing principles and thus can be studied with similar approaches. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as group decision-making, brain and cellular connectivity, network controllability and resiliency, online activism, recommendation systems, and cyber security.

This book presents original, peer-reviewed research papers from the 4th Purple Mountain Forum -International Forum on Smart Grid Protection and Control (PMF2019-SGPC), held in Nanjing, China on August 17-18, 2019. Addressing the latest research hotspots in the power industry, such as renewable energy integration, flexible interconnection of large scale power grids, integrated energy system, and cyber physical power systems, the papers share the latest research findings and practical application examples of the new theories, methodologies and algorithms in these areas. As such book a valuable reference for researchers, engineers, and university students.

Robotic animals are nowadays developed for various types of research, such as bio-inspired robotics, biomimetics and animal behavior studies. More specifically, in the case of collective animal behavior research, the robotic device can interact with animals by generating and exploiting signals relevant for social behavior. Once perceived by the animal society as conspecific, these robots can become powerful tools to study the animal behaviors, as they can at the same time monitor the changes in behavior and influence the collective choices of the animal society. In this book, we present novel robotized tools that can integrate shoals of fish in order to study their collective behaviors. We used the current state of the art on the zebrafish social behavior to define the specifications of the robots, and we performed stimuli analysis to improve their developments. Bio-inspired controllers were designed based on data extracted from experiments with zebrafish for the robots to mimic the zebrafish locomotion underwater. Experiments involving mixed groups of fish and robots qualified the robotic system to be integrated among a zebrafish shoal and to be able to influence the collective decisions of the fish. These results are very promising for the field of animal-robot interaction studies, as we showed the effect of the robots in long-duration experiments and repetitively, with the same order of response from the animals.

This book contains thirty-five selected papers presented at the International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems (EUROGEN 2017). This was one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS). Topics treated in the various chapters reflect the state of the art in theoretical and numerical methods and tools for optimization, and engineering design and societal applications. The volume focuses particularly on intelligent systems for multidisciplinary design optimization (mdo) problems based on multi-hybridized software, adjoint-based and one-shot methods, uncertainty quantification and optimization, multidisciplinary design optimization, applications of game theory to industrial optimization problems, applications in structural and civil engineering optimum design and surrogate models based optimization methods in aerodynamic design.

Many everyday dilemmas existing in the real world are complex and difficult to solve or fix, ranging from tax evasion to dispatching taxis to scheduling patient visits in hospitals, and much more. Within these complicated problems, however, lies the potential to be simplified or solved by intelligent agents and multi-agent systems. Theoretical and Practical Frameworks for Agent-Based Systems tackles these real problems and many more, bringing the theoretical research of intelligent agents to researchers and practitioners in academia, government, and innumerable industries. Professionals and experts in every field ranging from education to healthcare and beyond will find this reference to be essential in the understanding of agents, and researchers currently working in the field of intelligent agents will benefit from this exciting examination of practical applications.

This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy. The authors first show how federated learning provides a unique way to build personalized models using data without intruding on users' privacy. The authors then provide a comprehensive survey of state-of-the-art research on federated learning, giving the reader a general overview of the field. The book also investigates how a personalized federated learning framework is needed in cloud-edge architecture as well as in wireless-edge architecture for intelligent IoT applications. To cope with the heterogeneity issues in IoT environments, the book investigates emerging personalized federated learning methods that are able to mitigate the negative effects caused by heterogeneities in different aspects. The book provides case studies of IoT based human activity recognition to demonstrate the effectiveness of personalized federated learning for intelligent IoT applications, as well as multiple controller design and system analysis tools including model predictive control, linear matrix inequalities, optimal control, etc. This unique and complete co-design framework will benefit researchers, graduate students and engineers in the fields of control theory and engineering.

This book discusses the applications of different soft computing techniques for the web-based systems and services. The respective chapters highlight recent developments in the field of soft computing applications, from web-based information retrieval to online marketing and online healthcare. In each chapter author endeavor to explain the basic ideas behind the proposed applications in an accessible format for readers who may not possess a background in these fields. This carefully edited book covers a wide range of new applications of soft computing techniques in Web recommender systems, Online documents classification, Online documents summarization, Online document clustering, Online market intelligence, Web usage profiling, Web data extraction, Social network extraction, Question answering systems, Online health care, Web knowledge management, Multimedia information retrieval, Navigation guides, User profiles extraction, Web-based distributed information systems, Web security applications, Internet of Things Applications and so on. The book is aimed for researchers and practitioner who are engaged in developing and applying intelligent systems principles for solving real-life problems. Further, it has been structured so that each chapter can be read independently of the others.

This book presents recent research on computational intelligence (CI) algorithms in the field of sport. In the modern age, information technologies have greatly reduced the need for human effort in the carrying out of many daily tasks. These technologies have radically influenced the lives of humans, and the information society in general. Unfortunately, these advances have brought with them certain negative effects, including the encouragement of sedentary lifestyles and the attendant health problems such as obesity that these engender. Other modern maladies, chiefly cardiovascular disease, diabetes, and cancer, have also been on the increase. Today, sports are virtually the only activity that still connects modern humans to their original lifestyle, which was based on physical motion. This book tears familiarizing sports scientists with the foundations of computational intelligence, while at the same time presenting the problems that have arisen in the training domain to computer scientists. Lastly, the book proposes the use of an Artificial Sports Trainer designed to enhance the training of modern athletes who cannot afford the considerable expense of hiring a human personal trainer. This intelligent system can monitor performance and design and direct appropriate future training, thus promoting both healthy lifestyles and competitive success in athletes.

The author presents Probatio, a toolkit for building functional DMI (digital musical instruments) prototypes, artifacts in which gestural control and sound production are physically decoupled but digitally mapped. He uses the concept of instrumental inheritance, the application of gestural and/or structural components of existing instruments to generate ideas for new instruments. To support analysis and combination, he then leverages a traditional design method, the morphological chart, in which existing artifacts are split into parts, presented in a visual form and then recombined to produce new ideas. And finally he integrates the concept and the method in a concrete object, a physical prototyping toolkit for building functional DMI prototypes: Probatio. The author's evaluation of this modular system shows it reduces the time required to develop functional prototypes. The book is useful for researchers, practitioners, and graduate students in the areas of musical creativity and human-computer interaction, in particular those engaged in generating, communicating, and testing ideas in complex design spaces.

This book offers a collection of original peer-reviewed contributions presented at the 3rd International and 18th National Conference on Machines and Mechanisms (iNaCoMM), organized by Division of Remote Handling & Robotics, Bhabha Atomic Research Centre, Mumbai, India, from December 13th to 15th, 2017 (iNaCoMM 2017). It reports on various theoretical and practical features of machines, mechanisms and robotics; the contributions include carefully selected, novel ideas on and approaches to design, analysis, prototype development, assessment and surveys. Applications in machine and mechanism engineering, serial and parallel manipulators, power reactor engineering, autonomous vehicles, engineering in medicine, image-based data analytics, compliant mechanisms, and safety mechanisms are covered. Further papers provide in-depth analyses of data preparation, isolation and brain segmentation for focused visualization and robot-based neurosurgery, new approaches to parallel mechanism-based Master-Slave manipulators, solutions to forward kinematic problems, and surveys and optimizations based on historical and contemporary compliant mechanism-based design. The spectrum of contributions on theory and practice reveals central trends and newer branches of research in connection with these topics.

The increasing trend of multimedia data use is likely to accelerate creating an urgent need of providing a clear means of capturing, storing, indexing, retrieving, analyzing, and summarizing data through image data. ""Artificial Intelligence for Maximizing Content Based Image Retrieval"" discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field. Providing state-of-the-art research from leading international experts, this book offers a theoretical perspective and practical solutions for academicians, researchers, and industry practitioners.

This book presents the outcomes of the 17th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2018), which was held in Singapore on June 6-8, 2018. The aim of the conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science and to share their experiences, and to exchange new ideas and information in a meaningful way. The book includes findings on all aspects (theory, applications and tools) of computer and information science and discusses related practical challenges and the solutions adopted to solve them. The conference organizers selected the best papers from those accepted for presentation. The papers were chosen based on review scores submitted by members of the program committee and underwent a further rigorous round of review. From this second round, 13 of the conference's most promising papers were then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will make to the field of computer and information science.

This book provides an interdisciplinary approach to complexity, combining ideas from areas like complex networks, cellular automata, multi-agent systems, self-organization and game theory. The first part of the book provides an extensive introduction to these areas, while the second explores a range of research scenarios. Lastly, the book presents CellNet, a software framework that offers a hands-on approach to the scenarios described throughout the book. In light of the introductory chapters, the research chapters, and the CellNet simulating framework, this book can be used to teach undergraduate and master's students in disciplines like artificial intelligence, computer science, applied mathematics, economics and engineering. Moreover, the book will be particularly interesting for Ph.D. and postdoctoral researchers seeking a general perspective on how to design and create their own models.

These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Chapters in this volume include: Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression Hybrid Structural and Behavioral Diversity Methods in GP Multi-Population Competitive Coevolution for Anticipation of Tax Evasion Evolving Artificial General Intelligence for Video Game Controllers A Detailed Analysis of a PushGP Run Linear Genomes for Structured Programs Neutrality, Robustness, and Evolvability in GP Local Search in GP PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification Relational Structure in Program Synthesis Problems with Analogical Reasoning An Evolutionary Algorithm for Big Data Multi-Class Classification Problems A Generic Framework for Building Dispersion Operators in the Semantic Space Assisting Asset Model Development with Evolutionary Augmentation Building Blocks of Machine Learning Pipelines for Initialization of a Data Science Automation Tool Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.