The Intelligent Transportation System (ITS) Program is a cooperative effort by government, private industry, and academia to apply advanced technology to the task of resolving the problems of surface transportation. The objective is to improve travel efficiency and mobility, enhance safety, conserve energy, provide economic benefits, and protect the environment. The current demand for mobility has exceeded the available capacity of the roadway system. Because the highway system cannot be expanded, except in minor ways, the available capacity must be used more efficiently to handle the increased demand.
ITS applies advanced information processing, communication, sensing, and computer control technologies to the problems of surface transportation. Considerable research and development efforts will be required to produce these new technologies and to convert technologies developed in the defense and space programs to solve surface transportation problems.
ITS has been subdivided into six interlocking technology areas. This book addresses human factors concerns for four of these areas:
*" Advanced Traveler Information Systems" are a variety of systems that provide real time, in-vehicle information to drivers regarding navigation and route guidance, motorist services, roadway signing, and hazard warnings.
*" Advanced Vehicle Control Systems" refer to systems that aid drivers in controlling their vehicle particularly in emergency situations and ultimately taking over some or all of the driving tasks.
*" Commercial Vehicle Operations" address the application of ITS technologies to the special needs of commercial roadway vehicles including automated vehicle identification, location, weigh-in-motion, clearance sensing, and record keeping.
*" Advanced Traffic Management Systems" monitor, control and manage traffic on streets and highways to reduce congestion using vehicle route diversion, automated signal timing, changeable message signs, and priority control systems.
Two technical areas are not specifically addressed in individual chapters, but many aspects of them are covered in associated chapters:
*" Advanced Rural Transportation Systems" include systems that apply ITS technologies to the special needs of rural systems and include emergency notification and response, vehicle location, and traveler information.
*" Advanced Public Transportation Systems" enhance the effectiveness, attractiveness and economics of public transportation and include fleet management, automated fare collection, and real-time information systems.

This volume investigates our ability to capture, and then apply, expertise. In recent years, expertise has come to be regarded as an increasingly valuable and surprisingly elusive resource. Experts, who were the sole active dispensers of certain kinds of knowledge in the days before AI, have themselves become the objects of empirical inquiry, in which their knowledge is elicited and studied -- by knowledge engineers, experimental psychologists, applied psychologists, or other experts -- involved in the development of expert systems. This book achieves a marriage between experimentalists, applied scientists, and theoreticians who deal with expertise. It envisions the benefits to society of an advanced technology for capturing and disseminating the knowledge and skills of the best corporate managers, the most seasoned pilots, and the most renowned medical diagnosticians. This book should be of interest to psychologists as well as to knowledge engineers who are "out in the trenches" developing expert systems, and anyone pondering the nature of expertise and the question of how it can be elicited and studied scientifically. The book's scope and the pivotal concepts that it elucidates and appraises, as well as the extensive categorized bibliographies it includes, make this volume a landmark in the field of expert systems and AI as well as the field of applied experimental psychology.

Knowledge representation is a key area of modern AI, underlying the development of semantic networks. Description logics are languages that represent knowledge in a structured and formally well-understood way: they are the cornerstone of the Semantic Web. This is the first textbook describing this importan new topic and will be suitable for courses aimed at advanced undergraduate and beginning graduate students, or for self-study. It assumes only a basic knowledge of computer science concepts. After generla introducitons motivating and overviewing the subject, the authors describe a simple DL and how it works and can be used, utilizing a running example that recurs through the book. Methods of reasoning and their implementation and complexity are examined, Finally, the authors provide a non-trivial DL knowledge base and use it to illsutrate featues that have been introduced: this base is available for free online access in a form usable by modern ontology editors.

Provides a wide snapshot of building knowledge-based systems, inconsistency measures, methods for handling consistency, and methods for integrating knowledge bases. Provides the mathematical background to solve problems of restoring consistency and problems of integrating probabilistic knowledge bases in the integrating process. The research results presented in the book can be applied in decision support systems, semantic web systems, multimedia information retrieval systems, medical imaging systems, cooperative information systems, and more.

Multisensor Data Fusion: From Algorithms and Architectural Design to Applications covers the contemporary theory and practice of multisensor data fusion, from fundamental concepts to cutting-edge techniques drawn from a broad array of disciplines. Featuring contributions from the world's leading data fusion researchers and academicians, this authoritative book: Presents state-of-the-art advances in the design of multisensor data fusion algorithms, addressing issues related to the nature, location, and computational ability of the sensors Describes new materials and achievements in optimal fusion and multisensor filters Discusses the advantages and challenges associated with multisensor data fusion, from extended spatial and temporal coverage to imperfection and diversity in sensor technologies Explores the topology, communication structure, computational resources, fusion level, goals, and optimization of multisensor data fusion system architectures Showcases applications of multisensor data fusion in fields such as medicine, transportation's traffic, defense, and navigation Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies. The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution.

From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don't need an exotic new language or framework to get started; you can learn about genetic algorithms in a language you're already familiar with. Join us for an in-depth look at the algorithms, techniques, and methods that go into writing a genetic algorithm. From introductory problems to real-world applications, you'll learn the underlying principles of problem solving using genetic algorithms. Evolutionary algorithms are a unique and often overlooked subset of machine learning and artificial intelligence. Because of this, most of the available resources are outdated or too academic in nature, and none of them are made with Elixir programmers in mind. Start from the ground up with genetic algorithms in a language you are familiar with. Discover the power of genetic algorithms through simple solutions to challenging problems. Use Elixir features to write genetic algorithms that are concise and idiomatic. Learn the complete life cycle of solving a problem using genetic algorithms. Understand the different techniques and fine-tuning required to solve a wide array of problems. Plan, test, analyze, and visualize your genetic algorithms with real-world applications. Open your eyes to a unique and powerful field - without having to learn a new language or framework. What You Need: You'll need a macOS, Windows, or Linux distribution with an up-to-date Elixir installation.

With the proliferation of GPS devices in daily life, trajectory data that records where and when people move is now readily available on a large scale. As one of the most typical representatives, it has now become widely recognized that taxi trajectory data provides rich opportunities to enable promising smart urban services. Yet, a considerable gap still exists between the raw data available, and the extraction of actionable intelligence. This gap poses fundamental challenges on how we can achieve such intelligence. These challenges include inaccuracy issues, large data volumes to process, and sparse GPS data, to name but a few. Moreover, the movements of taxis and the leaving trajectory data are the result of a complex interplay between several parties, including drivers, passengers, travellers, urban planners, etc. In this book, we present our latest findings on mining taxi GPS trajectory data to enable a number of smart urban services, and to bring us one step closer to the vision of smart mobility. Firstly, we focus on some fundamental issues in trajectory data mining and analytics, including data map-matching, data compression, and data protection. Secondly, driven by the real needs and the most common concerns of each party involved, we formulate each problem mathematically and propose novel data mining or machine learning methods to solve it. Extensive evaluations with real-world datasets are also provided, to demonstrate the effectiveness and efficiency of using trajectory data. Unlike other books, which deal with people and goods transportation separately, this book also extends smart urban services to goods transportation by introducing the idea of crowdshipping, i.e., recruiting taxis to make package deliveries on the basis of real-time information. Since people and goods are two essential components of smart cities, we feel this extension is bot logical and essential. Lastly, we discuss the most important scientific problems and open issues in mining GPS trajectory data.

Negnevitsky shows students how to build intelligent systems drawing on techniques from knowledge-based systems, neural networks, fuzzy systems, evolutionary computation and now also intelligent agents. The principles behind these techniques are explained without resorting to complex mathematics, showing how the various techniques are implemented, when they are useful and when they are not. No particular programming language is assumed and the book does not tie itself to any of the software tools available. However, available tools and their uses are described, and program examples are given in Java. The lack of assumed prior knowledge makes this book ideal for any introductory courses in artificial intelligence or intelligent systems design, while the contemporary coverage means more advanced students will benefit by discovering the latest state-of-the-art techniques, particularly in intelligent agents and knowledge discovery.

Building Information Modeling (BIM) refers to the consistent and continuous use of digital information throughout the entire lifecycle of a built facility, including its design, construction and operation. In order to exploit BIM methods to their full potential, a fundamental grasp of their key principles and applications is essential. Accordingly, this book combines discussions of theoretical foundations with reports from the industry on currently applied best practices. The book's content is divided into six parts: Part I discusses the technological basics of BIM and addresses computational methods for the geometric and semantic modeling of buildings, as well as methods for process modeling. Next, Part II covers the important aspect of the interoperability of BIM software products and describes in detail the standardized data format Industry Foundation Classes. It presents the different classification systems, discusses the data format CityGML for describing 3D city models and COBie for handing over data to clients, and also provides an overview of BIM programming tools and interfaces. Part III is dedicated to the philosophy, organization and technical implementation of BIM-based collaboration, and discusses the impact on legal issues including construction contracts. In turn, Part IV covers a wide range of BIM use cases in the different lifecycle phases of a built facility, including the use of BIM for design coordination, structural analysis, energy analysis, code compliance checking, quantity take-off, prefabrication, progress monitoring and operation. In Part V, a number of design and construction companies report on the current state of BIM adoption in connection with actual BIM projects, and discuss the approach pursued for the shift toward BIM, including the hurdles taken. Lastly, Part VI summarizes the book's content and provides an outlook on future developments. The book was written both for professionals using or programming such tools, and for students in Architecture and Construction Engineering programs.

Since its inception, fuzzy logic has attracted an incredible amount of interest, and this interest continues to grow at an exponential rate. As such, scientists, researchers, educators and practitioners of fuzzy logic continue to expand on the applicability of what and how fuzzy can be utilised in the real-world. In this book, the authors present key application areas where fuzzy has had significant success. The chapters cover a plethora of application domains, proving credence to the versatility and robustness of a fuzzy approach. A better understanding of fuzzy will ultimately allow for a better appreciation of fuzzy. This book provides the reader with a varied range of examples to illustrate what fuzzy logic can be capable of and how it can be applied. The text will be ideal for individuals new to the notion of fuzzy, as well as for early career academics who wish to further expand on their knowledge of fuzzy applications. The book is also suitable as a supporting text for advanced undergraduate and graduate-level modules on fuzzy logic, soft computing, and applications of AI.

In the years since the bestselling first edition, fusion research and applications have adapted to service-oriented architectures and pushed the boundaries of situational modeling in human behavior, expanding into fields such as chemical and biological sensing, crisis management, and intelligent buildings.

Multisensor Data Fusion, Second Edition represents the most current concepts and theory as information fusion expands into the realm of network-centric architectures. It reflects new developments in distributed and detection fusion, situation and impact awareness in complex applications, and human cognitive concepts. With contributions from the world's leading fusion experts, this second edition expands to 31 chapters covering the fundamental theory and cutting-edge developments that are driving this field.

New to the Second Edition-

- Applications in electromagnetic systems and chemical and biological sensors

- Army command and combat identification techniques

- Techniques for automated reasoning

- Advances in Kalman filtering

- Fusion in a network centric environment

- Service-oriented architecture concepts

- Intelligent agents for improved decision making

- Commercial off-the-shelf (COTS) software tools

From basic information to state-of-the-art theories, this second edition continues to be a unique, comprehensive, and up-to-date resource for data fusion systems designers.

With the collapse of high-profile companies such as Enron and Tyco, worldwide anti-globalization protests, and recent revelations of questionable behavior by financial groups and auditors, corporate behavior has become the highest priority topic for businesspeople, investors, politicians and the public. Yet despite the critical importance of maintaining public and shareholder trust, most corporations make very little formal effort to actively manage the activities that can put their reputation, share price, and customer base at risk. Most corporations officially embrace the concept of Corporate Social Responsibility; but giving money away to local communities or worthy causes will not prevent an ethical disaster.
The problem is not social irresponsibility; the problem is a lack of knowledge about what is taking place in the company or at its subcontractor sites. What companies need to be thinking about is not a theoretical construct around Corporate Social Responsibility, or how they can spin public opinion by charitable actions. They need to be thinking about how they can create a practical knowledge and risk management framework in their company that allows them to avoid costly and reputation-damaging behavior in the first place.
Ultimately, this comes down to knowledge management. Whether violations of human rights, employment law, or environmental standards - or simply accounting shenanigans - invariably the reason that these activities are not anticipated and avoided is simply that executives and board members do not realize what is happening in the organization, and what the likely implications of actions will be. And the larger the organization, the more extensive thatlack of knowledge.
The good news is that developing a strategic approach to corporate integrity is neither exceptionally expensive nor particularly difficult. The problem is that companies that are already using sophisticated information technology and knowledge management tools for gathering internal and external information have focused those systems and practices almost exclusively on operational issues and increasing productivity. But these same knowledge management techniques - built around emerging ethical guidelines being developed by international standards groups - can be used by companies to create an effective global policy for building and maintaining corporate integrity. This means applying knowledge management techniques in three important areas:
* First, they need to mobilize key employee knowledge and the vast amount of information available on potentially sensitive issues in a way that allows key decision-makers to "sense and respond" quickly and correctly to developing risks.
* Second, it means creating objective, scenario-based guidelines for ethical behavior, communicating those guidelines using knowledge management techniques among key organizational leaders, and providing a workable system of incentives for managers to surface potentially dangerous issues.
* Third, companies need to adopt emerging guidelines such as AA1000 that provide for ethical procedures and performance indicators that enable companies to audit and monitor their own behavior, and also to provide shareholders and the buying public with an objective report on the company's ethical performance. Much like ISO 9000, Six Sigma and other performance and productivity and practicestandards of the 1990s, these new global ethics standards will inevitably become a baseline by which investors and customers judge a company's potential for future growth and stability. High marks on auditable ethical performance set against these guidelines will become an important way for companies to differentiate themselves from their competition in the future.
Developing a workable program for corporate ethics will be one of the most important issues of this decade, and will be "the next big thing" for large organizations. A drive toward standardized reporting of corporate ethics practices was coming anyway; the recent public corporate disasters will only encourage corporate executive teams to scramble to demonstrate to customers and shareholders that their organization takes these issues seriously.
This book, therefore, will be a primer for business people and business students worldwide who will shortly be tasked with devising or participating in those types of corporate integrity initiatives, and will explain how knowledge management is indispensable as a tool for helping corporations to manage their risk and integrity policies. Through a mixture of leading practice case studies and a clear framework, it will show how a corporation can begin to combine leading practices in risk and knowledge management with emerging international guidelines in order to develop and manage a program of corporate integrity.
* The first book to show how knowledge management and corporate integrity intersect
* Shows executives how to develop a strategic approach to corporate integrity in this post-Enron age
* Neef, an expert on knowledge management, explains how a company canre-engineer existing knowledge management systems to build and maintain an effective corporate integrity program

The Handbook of Applied Expert Systems is a landmark work dedicated solely to this rapidly advancing area of study. Edited by Jay Liebowitz, a professor, author, and consultant known around the world for his work in the field, this authoritative source covers the latest expert system technologies, applications, methodologies, and practices. The book features contributions from more than 40 of the world's foremost expert systems authorities in industry, government, and academia.
The Handbook is organized into two major sections. The first section explains expert systems technologies while the second section focuses on applied examples in a wide variety of industries. Key topics covered include fuzzy systems, genetic algorithm development, machine learning, knowledge representation, and much more.

The Intelligent Transportation System (ITS) Program is a cooperative effort by government, private industry, and academia to apply advanced technology to the task of resolving the problems of surface transportation. The objective is to improve travel efficiency and mobility, enhance safety, conserve energy, provide economic benefits, and protect the environment. The current demand for mobility has exceeded the available capacity of the roadway system. Because the highway system cannot be expanded, except in minor ways, the available capacity must be used more efficiently to handle the increased demand.
ITS applies advanced information processing, communication, sensing, and computer control technologies to the problems of surface transportation. Considerable research and development efforts will be required to produce these new technologies and to convert technologies developed in the defense and space programs to solve surface transportation problems.
ITS has been subdivided into six interlocking technology areas. This book addresses human factors concerns for four of these areas:
*" Advanced Traveler Information Systems" are a variety of systems that provide real time, in-vehicle information to drivers regarding navigation and route guidance, motorist services, roadway signing, and hazard warnings.
*" Advanced Vehicle Control Systems" refer to systems that aid drivers in controlling their vehicle particularly in emergency situations and ultimately taking over some or all of the driving tasks.
*" Commercial Vehicle Operations" address the application of ITS technologies to the special needs of commercial roadway vehicles including automated vehicle identification, location, weigh-in-motion, clearance sensing, and record keeping.
*" Advanced Traffic Management Systems" monitor, control and manage traffic on streets and highways to reduce congestion using vehicle route diversion, automated signal timing, changeable message signs, and priority control systems.
Two technical areas are not specifically addressed in individual chapters, but many aspects of them are covered in associated chapters:
*" Advanced Rural Transportation Systems" include systems that apply ITS technologies to the special needs of rural systems and include emergency notification and response, vehicle location, and traveler information.
*" Advanced Public Transportation Systems" enhance the effectiveness, attractiveness and economics of public transportation and include fleet management, automated fare collection, and real-time information systems.

Design is believed to be one of the most interesting and challenging problem-solving activities ever facing artificial intelligence (AI) researchers. Knowledge-based systems using rule-based and model-based reasoning techniques have been applied to build design automation and/or design decision support systems. Although such systems have met with some success, difficulties have been encountered in terms of formalizing such generalized design experiences as rules, logic, and domain models. Recently, researchers have been exploring the idea of using case-based reasoning (CBR) techniques to complement or replace other approaches to design support. CBR can be considered as an alternative to paradigms such as rule-based and model-based reasoning. Rule-based expert systems capture knowledge in the form of if-then rules which are usually identified by a domain expert. Model-based reasoning aims at formulating knowledge in the form of principles to cover the various aspects of a problem domain. These principles, which are more general than if-then rules, comprise a model which an expert system may use to solve problems. Model-based reasoning (MBR) is sometimes called reasoning from first principles. Instead of generalizing knowledge into rules or models, CBR is an experience-based method. Thus, specific cases, corresponding to prior problem-solving experiences, comprise the main knowledge sources in a CBR system. This volume includes a collection of chapters that describe specific projects in which case-based reasoning is the focus for the representation and reasoning in a particular design domain. The chapters provide a broad spectrum of applications and issues in applying and extending the concept of CBR to design. Each chapter provides its own introduction to CBR concepts and principles.

Even to the casual observer of the automotive industry, it is clear that driving in the 21st century will be radically different from driving as we know it today. Significant advances in diverse technologies such as digital maps, communication links, processors, image processing, chipcards, traffic management, and vehicle positioning and tracking, are enabling extensive development of intelligent transport systems (ITS). Proponents of ITS view these technologies as freeing designers to re-define the role and function of transport in society and to address the urgent problems of congestion, pollution, and safety. Critics, on the other hand, worry that ITS may prove too complex, too demanding, and too distracting for users, leading to loss of skill, increased incidence of human error, and greater risk of accidents.
The role of human factors is widely acknowledged to be critical to the successful implementation of such technologies. However, too little research is directed toward advancing the science of human-ITS interaction, and too little is published which is useful to system designers. This book is an attempt to fill this critical gap. It focuses on the intelligent driver interface (IDI) because the ergonomics of IDI design will influence safety and usability perhaps more than the technologies which underlie it.
The chapters cover a broad range of topics, from cognitive considerations in the design of navigation and route guidance, to issues associated with collision warning systems, to monitoring driver fatigue. The chapters also differ in intent -- some provide design recommendations while others describe research findings or new approaches for IDI research and development. Based in part on papers presented at a symposium on the ergonomics of in-vehicle human systems held under the auspices of the 12th Congress of the International Ergonomics Association, the book provides an international perspective on related topics through inclusion of important contributions from Europe, North America, and Japan.
Many of the chapters discuss issues associated with navigation and route guidance because such systems are the most salient and arguably the most complex examples of IDI. However, the findings and research methodologies are relevant to other systems as well, making this book of interest to a wide audience of researchers, design engineers, transportation authorities, and academicians involved with the development or implementation of ITS.

This book bridges the gap between knowledge management and technology. It embraces the complete lifecycle of knowledge, information, and data from how knowledge flows through an organization to how end users want to handle it and experience it. Whether your intent is to design and implement a single technology or a complete collection of KM systems, this book provides the foundations necessary for success. It will help you understand your organization's needs and opportunities, strategize and prioritize features and functions, design with the end user in mind, and finally build a system that your users will embrace and which will realize meaningful business value for your organization. The book is the culmination of the authors' collective careers, a combined sixty years of experience doing exactly what is detailed in this book. Their guidance has been honed by their own successes and failures as well as many others they have researched in order to provide a comprehensive study on KM transformations and the technologies that help to enable them. They have successfully applied this knowledge as the founders and leaders of the world's largest dedicated knowledge management consultancy, which runs these projects for many of the world's most complex organizations. They are writing as practitioners directly to other practitioners with the intent to enable them to apply and benefit from their knowledge and experience. "Compelling reading for KM practitioners looking to ensure their technology decisions support their business and organizational objectives." - Margot Brown, Director of Knowledge Management, World Bank Group "We are two years into our KM Transformation and if I'd had this book beforehand, it would have made the journey smoother and faster! This is a great playbook for how to plan, organize, and execute a KM transformation." - Stephanie Hill, Senior Director, Global Customer Services, PayPal

This volume investigates our ability to capture, and then apply, expertise. In recent years, expertise has come to be regarded as an increasingly valuable and surprisingly elusive resource. Experts, who were the sole active dispensers of certain kinds of knowledge in the days before AI, have themselves become the objects of empirical inquiry, in which their knowledge is elicited and studied -- by knowledge engineers, experimental psychologists, applied psychologists, or other experts -- involved in the development of expert systems. This book achieves a marriage between experimentalists, applied scientists, and theoreticians who deal with expertise. It envisions the benefits to society of an advanced technology for capturing and disseminating the knowledge and skills of the best corporate managers, the most seasoned pilots, and the most renowned medical diagnosticians. This book should be of interest to psychologists as well as to knowledge engineers who are "out in the trenches" developing expert systems, and anyone pondering the nature of expertise and the question of how it can be elicited and studied scientifically. The book's scope and the pivotal concepts that it elucidates and appraises, as well as the extensive categorized bibliographies it includes, make this volume a landmark in the field of expert systems and AI as well as the field of applied experimental psychology.

Introduces manufacturing engineers to the use of expert systems to control autoclaves in the production of items made of thermosetting or thermoplastic composite material. Does not provide a complete solution, but discusses the rationale behind models, the rules and numerical procedures, and the sof

This, the 38th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains extended and revised versions of six papers selected from the 68 contributions presented at the 27th International Conference on Database and Expert Systems Applications, DEXA 2016, held in Porto, Portugal, in September 2016. Topics covered include query personalization in databases, data anonymization, similarity search, computational methods for entity resolution, array-based computations in big data analysis, and pattern mining.

This book focuses on how real-time task schedules for reconfigurable hardware-based embedded platforms may be affected due to the vulnerability of hardware and proposes self-aware security strategies to counteract the various threats. The emergence of Industry 4.0 has witnessed the deployment of reconfigurable hardware or field programmable gate arrays (FPGAs) in diverse embedded applications. These are associated with the execution of several real-time tasks arranged in schedules. However, they are associated with several issues. Development of fully and partially reconfigurable task schedules are discussed that eradicates the existing problems. However, such real-time task schedules may be jeopardized due to hardware threats. Analysis of such threats is discussed and self-aware security techniques are proposed that can detect and mitigate such threats at runtime.

The two-volume set LNCS 13341 and 13342 constitutes the refereed proceedings of the Joint International Conference on Digital Inclusion, Assistive Technology, and Accessibility, ICCHP-AAATE 2022. The conference was held in Lecco, Italy, in July 2022. The 112 papers presented were carefully reviewed and selected from 285 submissions. Included also are 18 introductions. The papers are organized in the following topical sections: Part I: Art Karshmer Lectures in Access to Mathematics, Science and Engineering; Digital Solutions for Inclusive Mobility: solutions and accessible maps for indoor and outdoor mobility; implementation and innovation in the area of independent mobility through digital technologies; haptic and digital access to art and artefacts; accessibility of co-located meetings; interactions for text input and alternative pointing; cognitive disabilities and accessibility; augmentative and alternative communication (AAC): emerging trends, opportunities and innovations; language accessibility for the deaf and hard-of-hearing. Part II: Digital accessibility: readability and understandability; serious and fun games; internet of things: services and applications for people with disabilities and elderly persons; technologies for inclusion and participation at work and everyday activities; robotic and virtual reality technologies for children with disabilities and older adults; development, evaluation and assessment of assistive technologies; ICT to support inclusive education - universal learning design (ULD); design for assistive technologies and rehabilitation; assistive technologies and inclusion for older people. 11 Chapters are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book highlights new trends and challenges in research on agents and the new digital and knowledge economy. It includes papers on business process management, agent-based modeling and simulation, and anthropic-oriented computing that were originally presented at the 15th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2021), being held as a Virtual Conference in June 14-16, 2021. The respective papers cover topics such as software agents, multi-agent systems, agent modeling, mobile and cloud computing, big data analysis, business intelligence, artificial intelligence, social systems, computer embedded systems, and nature-inspired manufacturing, all of which contribute to the modern digital economy.