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This book delves into the very core of our digital existence, unearthing the essence of a digital persona. It's a realm where authenticity meets multiplicity, as we decipher the nuanced art of crafting and managing our online identities. We confront issues of privacy and ethics, exploring the profound impact of our digital footprints on our lives and society. The integration of AI paves the way for an intriguing future, with predictions that challenge our understanding of self in the digital age. Welcome to a world where your digital personality is more than just data; it's a reflection of who you are and who you can be. The main goal of this book is to enable more seamless and natural human–computer interaction. This will provide better personalized experience. Further, this will influence the performance of the user, wherein they will have the support of the machines to achieve their tasks in the most efficient way. This book is the first of a kind in introducing Digital Personality. It provides an overview of the character dimensions and how state-of-the-art technologies would accommodate such a research field. It includes novel representation of character from various perspectives. It also provides instances of applications of this emerging research field.

In the face of a world overwhelmed by environmental challenges, the need for sustainability has reached a critical juncture. This multidimensional concept demands a delicate equilibrium between environmental preservation, economic viability, and social equity. Navigating this intricate terrain necessitates innovative solutions that bridge the present and the future. The urgency is palpable as we grapple with the repercussions of unsustainable practices. Sustainability demands innovative solutions to bridge the gap between the needs of the present and the aspirations of future generations. Intelligent Methods and Alternative Economic Models for Sustainability recognizes the pressing need for transformative strategies that navigate the intricate intersections of environmental, economic, and social considerations. The established linear'take-make-dispose'model has proven unsustainable, necessitating a paradigm shift towards regenerative systems. Amid these challenges, the book identifies a critical gap—intelligent methodologies and alternative economic models that can pave the way for a sustainable future are often scattered in disparate fields, lacking a cohesive exploration. As such, the urgency lies in blending these disparate strands into a comprehensive tapestry to guide solutions for sustainability across diverse sectors. Intelligent Methods and Alternative Economic Models for Sustainability emerges as the definitive solution to this urgent problem. By synergizing intelligent methods and alternative economic models, the book provides a cohesive framework to address the multifaceted challenges of sustainability. It delves into the transformative power of metaheuristics, big data, and the Internet of Things (IoT) in optimizing complex systems while advocating for circular economic models that minimize waste and maximize resource efficiency. The book transcends theoretical discourse, offering real-world insights into successful sustainability initiatives. This comprehensive approach caters not only to researchers in computer sciences, economics, and sustainability but also empowers policymakers with actionable strategies and engages the broader public, fostering awareness and understanding of sustainability issues that impact us all.

This book addresses increasingly relevant social problems enabled by social media through the lens of system science research and modeling. Instead of evaluating existing patterns from existing social media data, the book focuses on exploring the possibility of various policies. Specifically, it provides fresh insight into the political echo chamber and polarization in social media using agent-based modeling and scenario analysis. The book contains a practical framework to study the factors influencing echo chambers and polarization formation occurring in social media communication. By modeling individual social media users'information consumption, the influence of various behaviors and policies are captured as macro-phenomena. The book also introduces a comprehensive agent-based reinterpretation of the Zaller model, a classic in public opinion research. In addition, the book demonstrates two real-life applications of the model using empirical observations: resolving theconflicting observations of the online echo chamber effect, and modeling the influence of vaccine-related Facebook pages on users'opinions about vaccination.

There are many different ways of generating representations. This includes representations generated by living beings while comprehending reality in order to act; representations generated by the Universe during its extensive unfolding, creating physical elements and living beings; and the direct representation of elements through an animal's sixth sense. To this list we must now add the creation of artificial consciousness, which generates representations that resemble the mental representations of humans. These representations allow robotic systems to communicate directly with each other.Fundamental Generation Systems develops a theory which presents, from the beginning, the function of this sixth sense called the “sense of informational comprehension”. This sense is understood as an ability to use the informational foundations of the Universe via a dedicated cerebral domain found in every animal.

This book explores the intelligent autonomous control problems for spacecraft with multiple constraints, such as pointing/path constraints, linear/angular velocity constraints, performance constraints, etc. It provides an almost self-contained presentation of dynamics modeling, controller design and analysis, as well as simulation studies. The book aims to offer a valuable guide for researchers and aerospace engineers to address the theoretical and technical difficulties in different applications, ranging from spacecraft attitude reorientation and tracking to spacecraft proximity operations, and is mainly intended for technical and engineering staff engaged in spacecraft dyanmics and control areas.

One of the core problems in artificial intelligence is the modelling of human reasoning and intelligent behaviour. The representation of knowledge, and reasoning about it, are of crucial importance in achieving this. This book, Semantics of Belief Change Operators for Intelligent Agents: Iteration, Postulates, and Realizability, addresses a number of significant research questions in belief change theory from a semantic point of view; in particular, the connection between different types of belief changes and plausibility relations over possible worlds is investigated. This connection is characterized for revision over general classical logics, showing which relations are capturing AGM revision. In addition, those classical logics for which the correspondence between AGM revision and total preorders holds are precisely characterized. AGM revision in the Darwiche-Pearl framework for belief change over arbitrary sets of epistemic states is considered, demonstrating, especially, that for some sets of epistemic states, no AGM revision operator exists. A characterization of those sets of epistemic states for which AGM revision operators exist is presented. The expressive class of dynamic limited revision operators is introduced to provide revision operators for more sets of epistemic states. Specifications for the acceptance behaviour of various belief-change operators are examined, and those realizable by dynamic-limited revision operators are described. The iteration of AGM contraction in the Darwiche-Pearl framework is explored in detail, several known and novel iteration postulates for contraction are identified, and the relationships among these various postulates are determined. With a convincing presentation of ideas, the book refines and advances existing proposals of belief change, develops novel concepts and approaches, rigorously defines the concepts introduced, and formally proves all technical claims, propositions and theorems, significantly advancing the state-of-the-art in this field.

An introduction to neurorobotics that presents approaches and design principles for developing intelligent autonomous systems grounded in biology and neuroscience.Neurorobotics is an interdisciplinary field that draws on artificial intelligence, cognitive sciences, computer science, engineering, psychology, neuroscience, and robotics. Because the brain is closely coupled to the body and situated in the environment, neurorobots—autonomous systems modeled after some aspect of the brain—offer a powerful tool for studying neural function and may also be a means for developing autonomous systems with intelligence that rivals that of biological organisms. This textbook introduces approaches and design principles for developing intelligent autonomous systems grounded in biology and neuroscience. It is written for anyone interested in learning about this topic and can be used in cognitive robotics courses for students in psychology, cognitive science, and computer science.Neurorobotics covers the background and foundations of the field, with information on early neurorobots, relevant principles of neuroscience, learning rules and mechanisms, and reinforcement learning and prediction; neurorobot design principles grounded in neuroscience and principles of neuroscience research; and examples of neurorobots for navigation, developmental robotics, and social robots, presented with the cognitive science and neuroscience background that inspired them. A supplementary website offers videos, robot simulations, and links to software repositories with neurorobot examples.

This book aims to explore and discuss theories and technologies for the development of socially competent and culture-aware embodied conversational agents for elderly care. To tackle the challenges in ageing societies, this book was written by experts who have a background in assistive technologies for elderly care, culture-aware computing, multimodal dialogue, social robotics and synthetic agents. Chapter 1 presents a vision of an intelligent agent to illustrate the current challenges for the design and development of adaptive systems. Chapter 2 examines how notions of trust and empathy may be applied to human–robot interaction and how it can be used to create the next generation of emphatic agents, which address some of the pressing issues in multicultural ageing societies. Chapter 3 discusses multimodal machine learning as an approach to enable more effective and robust modelling technologies and to develop socially competent and culture-aware embodied conversational agents for elderly care. Chapter 4 explores the challenges associated with real-world field tests and deployments. Chapter 5 gives a short introduction to socio-cognitive language processing that describes the idea of coping with everyday language, irony, sarcasm, humor, paralinguistic information such as the physical and mental state and traits of the dialogue partner, and social aspects. This book grew out of the Shonan Meeting seminar entitled “Multimodal Agents for Ageing and Multicultural Societies” held in 2018 in Japan. Researchers and practitioners will be helped to understand the emerging field and the identification of promising approaches from a variety of disciplines such as human–computer interaction, artificial intelligence, modelling, and learning.

Gain an in-depth overview of reinforcement learning for autonomous agents in game development with Unity.This book starts with an introduction to state-based reinforcement learning algorithms involving Markov models, Bellman equations, and writing custom C# code with the aim of contrasting value and policy-based functions in reinforcement learning. Then, you will move on to path finding and navigation meshes in Unity, setting up the ML Agents Toolkit (including how to install and set up ML agents from the GitHub repository), and installing fundamental machine learning libraries and frameworks (such as Tensorflow). You will learn about: deep learning and work through an introduction to Tensorflow for writing neural networks (including perceptron, convolution, and LSTM networks), Q learning with Unity ML agents, and porting trained neural network models in Unity through the Python-C# API. You will also explore the OpenAI Gym Environment used throughout the book.Deep Reinforcement Learning in Unity provides a walk-through of the core fundamentals of deep reinforcement learning algorithms, especially variants of the value estimation, advantage, and policy gradient algorithms (including the differences between on and off policy algorithms in reinforcement learning). These core algorithms include actor critic, proximal policy, and deep deterministic policy gradients and its variants. And you will be able to write custom neural networks using the Tensorflow and Keras frameworks. Deep learning in games makes the agents learn how they can perform better and collect their rewards in adverse environments without user interference. The book provides a thorough overview of integrating ML Agents with Unity for deep reinforcement learning.What You Will Learn Understand how deep reinforcement learning works in gamesGrasp the fundamentals of deep reinforcement learning Integrate these fundamentals with the Unity ML Toolkit SDKGain insights into practical neural networks for training Agent Brain in the context of Unity ML AgentsCreate different models and perform hyper-parameter tuningUnderstand the Brain-Academy architecture in Unity ML AgentsUnderstand the Python-C# API interface during real-time training of neural networksGrasp the fundamentals of generic neural networks and their variants using TensorflowCreate simulations and visualize agents playing games in Unity Who This Book Is ForReaders with preliminary programming and game development experience in Unity, and those with experience in Python and a general idea of machine learning

The paradigm of self-organisation is fundamental to theories of collective action in economic science and democratic governance in political science. Self-organisation in these social systems critically depends on voluntary compliance with conventional rules: that is, rules which are made up, mutually agreed, and modifiable'on the fly'. How, then, can we use the self-organisation observed in such social systems as an inspiration for decentralised computer systems, which can face similar problems of coordination, cooperation and collaboration between autonomous peers?Self-Organising Multi-Agent Systems presents an innovative and systematic approach to transforming theories of economics and politics (and elements of philosophy, psychology, and jurisprudence) into an executable logical specification of conventional rules. It shows how sets of such rules, called institutions, provide an algorithmic basis for designing and implementing cyber-physical systems, enabling intelligent software processes (called agents) to manage themselves in the face of competition for scarce resources. It also provides a basis for implementing socio-technical systems with interacting human and computational intelligences in a way that is sustainable, fair and legitimate.This interdisciplinary book is essential reading for anyone interested in the'planned emergence'of global properties, commonly-shared values or successful collective action, especially as a product of social construction, knowledge management and political arrangements. For those studying both computer science and social sciences, this book offers a radically new gateway to a transformative understanding of complex system development and social system modelling.Understanding how a computational representation of qualitative values like justice and democracy can lead to stability and legitimacy of socio-technical systems is among the most pressing software engineering challenges of modern times. This book can be read as an invitation to make the Digital Society better.Related Link(s)

By gathering important contributions from leading international experts in the field, this book explores the application of conversational agents in the specific role of tutor in e-learning processes (e.g. MOOCs, Mobile Assisted Learning). The aim is to investigate: [a] their technological implementation; [b] the underlying instructional design; [c] the type of activities that conversational agents carry out; [d] the outcomes of different experimental pilots and prototypes.

The Handbook on Socially Interactive Agents provides a comprehensive overview of the research fields of Embodied Conversational Agents, Intelligent Virtual Agents, and Social Robotics. Socially Interactive Agents (SIAs), whether virtually or physically embodied, are autonomous agents that are able to perceive an environment including people or other agents, reason, decide how to interact, and express attitudes such as emotions, engagement, or empathy. They are capable of interacting with people and one another in a socially intelligent manner using multimodal communicative behaviors, with the goal to support humans in various domains.Written by international experts in their respective fields, the book summarizes research in the many important research communities pertinent for SIAs, while discussing current challenges and future directions. The handbook provides easy access to modeling and studying SIAs for researchers and students, and aims at further bridging the gap between the research communities involved.In two volumes, the book clearly structures the vast body of research. The first volume starts by introducing what is involved in SIAs research, in particular research methodologies and ethical implications of developing SIAs. It further examines research on appearance and behavior, focusing on multimodality. Finally, social cognition for SIAs is investigated using different theoretical models and phenomena such as theory of mind or pro-sociality. The second volume starts with perspectives on interaction, examined from different angles such as interaction in social space, group interaction, or long-term interaction. It also includes an extensive overview summarizing research and systems of human–agent platforms and of some of the major application areas of SIAs such as education, aging support, autism, and games.

The main concepts and techniques of multi-agent oriented programming, which supports the multi-agent systems paradigm at the programming level.A multi-agent system is an organized ensemble of autonomous, intelligent, goal-oriented entities called agents, communicating with each other and interacting within an environment. This book introduces the main concepts and techniques of multi-agent oriented programming, (MAOP) which supports the multi-agent systems paradigm at the programming level. MAOP provides a structured approach based on three integrated dimensions, which the book examines in detail: the agent dimension, used to design the individual (interacting) entities; the environment dimension, which allows the development of shared resources and connections to the real world; and the organization dimension, which structures the interactions among the autonomous agents and the shared environment. The book puts the approach into practice using the JaCaMo programming model and platform. It employs an easy-to-follow, step-by-step style, showing solutions to increasingly complex scenarios. The book also discusses the integration of MAOP into existing technologies and application domains, including mobile computing, web-based computing, and robotics. Finally, it considers artificial intelligence (AI)–related classical problems from an MAOP perspective and discusses an agent-oriented approach to software engineering.

There are many myths and mistakes which make the topics of artificial intelligence complex and confusing. But the truth is that the foundations of AI are not rocket science. People do not need a PhD to understand how a basic neural network works. In fact, one does not even need computer skills to learn this.Cunning Machines: Your Pocket Guide to the World of Artificial Intelligence explains the main concepts: what does AI really mean, where do we find it, how do scientists try to evaluate it, what are its main limitations and what future we can expect with it? It also describes the most popular AI techniques in an easy-to-digest form: Artificial neural networks Genetic algorithms The Monte Carlo method Natural language processing Ontologies and their applications This book is for everyone. Still, it may be especially valuable to teachers who wish to enrich their classes with some interesting and popular topics, sales managers and business analysts who wish to better understand the IT world, and finally politicians and journalists who take part in debates on the latest technologies.Jędrzej Osiński earned a PhD in artificial intelligence, has worked on government grants and has published 14 scientific papers to date. He is also the co-author of two books. At the same time, he has over ten years of experience working in IT companies of different sizes, domains (the web, telecoms, banking, e-learning), organisation structures and locations (Poland, Ireland and the UK). He is also involved in various initiatives promoting AI, science and modern technologies including blog posts, invited talks and TV and radio appearances

Explore the adoption of chatbots in business by focusing on the design, deployment, and continuous improvement of chatbots in a business, with a single use-case from the banking and insurance sector. This book starts by identifying the business processes in the banking and insurance industry. This involves data collection from sources such as conversations from customer service centers, online chats, emails, and other NLP sources. You'll then design the solution architecture of the chatbot. Once the architecture is framed, the author goes on to explain natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) with examples. In the next sections, you'll design and implement the backend framework of a typical chatbot from scratch. You will also explore some popular open-source chatbot frameworks such as Dialogflow and LUIS. The authors then explain how you can integrate various third-party services and enterprise databases with the custom chatbot framework. In the final section, you'll discuss how to deploy the custom chatbot framework on the AWS cloud.By the end of Building an Enterprise Chatbot, you will be able to design and develop an enterprise-ready conversational chatbot using an open source development platform to serve the end user.What You Will LearnIdentify business processes where chatbots could be usedFocus on building a chatbot for one industry and one use-case rather than building a ubiquitous and generic chatbot Design the solution architecture for a chatbotIntegrate chatbots with internal data sources using APIsDiscover the differences between natural language understanding (NLU), natural language processing (NLP), and natural language generation (NLG) Work with deployment and continuous improvement through representational learningWho This Book Is ForData scientists and enterprise architects who are currently looking to deploy chatbot solutions to their business.

Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight into natural language processing with the natural language toolkit (NLTK) for building a custom language processing platform for your chatbot. With this foundation, you will take a look at different natural language processing techniques so that you can choose the right one for you. The next stage is to learn to build a chatbot using the API.ai platform and define its intents and entities. During this example, you will learn to enable communication with your bot and also take a look at key points of its integration and deployment.The final chapter of Building Chatbots with Python teaches you how to build, train, and deploy your very own chatbot. Using open source libraries and machine learning techniques you will learnto predict conditions for your bot and develop a conversational agent as a web application. Finally you will deploy your chatbot on your own server with AWS. What You Will LearnGain the basics of natural language processing using Python Collect data and train your data for the chatbotBuild your chatbot from scratch as a web appIntegrate your chatbots with Facebook, Slack, and TelegramDeploy chatbots on your own serverWho This Book Is ForIntermediate Python developers who have no idea about chatbots. Developers with basic Python programming knowledge can also take advantage of the book.

Multi-Agent Systems (MAS) use networked multiple autonomous agents to accomplish complex tasks in areas such as space-based applications, smart grids, and machine learning. The overall system goal is achieved using local interactions among the agents. The last two decades have witnessed rapid development of MASs in automatic control. Tracing the roots of such systems back more than 50 years, this monograph provides the reader with an in-depth and comprehensive survey of the research in Multi-Agent Systems. The focus is on the research conducted in the two decades. It introduces the basic concepts and definitions to the reader before going on to describe how MAS has been used in most forms of systems. The monograph offers a concise reference for understanding the use of MASs and the contemporary research issues for further investigation. In addition to covering the basic theory, the authors also cover applications in multi-robot systems, sensor networks, smart grid, machine learning, social networks, and many-core microprocessors. On the Control of Multi-Agent Systems provides researchers and students in systems and control a modern, comprehensive survey of one of the most important current day topics.

Learn about bot programming, using all the latest and greatest programming languages, including Python, Go, and Clojure, so you can feel at ease writing your Telegram bot in a way that suits you.This book shows how you can use bots for just about everything: they connect, they respond, they enhance your job search chances, they do technical research for you, they remind you about your last train, they tell the difference between a horse and a zebra, they can tell jokes, and they can cheer you up in the middle of the night. Bots used to be hard to set up and enhance, but with the help of Building Telegram Bots you'll see how the Telegram platform is now making bot creation easier than ever. You will begin by writing a simple bot at the start and then gradually build upon it. The simple yet effective Telegram Bot API makes it very easy to develop bots in a number of programming languages. Languages featured inthe book include Node.js, Java, Rust, and Elixir. This book encourages you to not only learn the basic process of creating a bot but also lets you spend time exploring its possibilities. By the end of the book you will be able create your own Telegram Bot with the programming language of your choice. What You Will LearnCarry out simple bot design and deployment in various programming languages including Ruby, D, Crystal, Nim, and C++Create engaging bot interactions with your usersAdd payments and media capabilities to your botsMaster programming language abstractionWho This Book Is ForEngineers who want to get things done. People who are curious. Programming beginners. Advanced engineers with little time to do research.

The book focuses on smart computing for crowdfunding usage, looking at the crowdfunding landscape, e.g., reward-, donation-, equity-, P2P-based and the crowdfunding ecosystem, e.g., regulator, asker, backer, investor, and operator. The increased complexity of fund raising scenario, driven by the broad economic environment as well as the need for using alternative funding sources, has sparked research in smart computing techniques. Covering a wide range of detailed topics, the authors of this book offer an outstanding overview of the current state of the art; providing deep insights into smart computing methods, tools, and their applications in crowdfunding; exploring the importance of smart analysis, prediction, and decision-making within the fintech industry. This book is intended to be an authoritative and valuable resource for professional practitioners and researchers alike, as well as finance engineering, and computer science students who are interested in crowdfunding and other emerging fintech topics.

This book offers valuable new insights into the design of culturally-aware systems. In its first part, it is devoted to presenting selected Culturally-Aware Intelligent Systems devised in the field of Artificial Intelligence and its second part consists of two sub-parts that offer a source of inspiration for building modelizations of Culture and of its influence on the human mind and behavior, to be used in new Culturally-Aware Intelligent Systems. Those sub-parts present the results of experiments conducted in two fields that study Culture and its influence on the human mind's functions: Cultural Neuroscience and Cross-Cultural Psychology. In this era of globalization, people from different countries and cultures have the opportunity to interact directly or indirectly in a wide variety of contexts. Despite differences in their ways of thinking and reasoning, their behaviors, their values, lifestyles, customs and habits, languages, religions – in a word, their cultures – they must be able to collaborate on projects, to understand each other's views, to communicate in such a way that they don't offend each other, to anticipate the effects of their actions on others, and so on. As such, it is of primary importance to understand how culture affects people's mental activities, such as perception, interpretation, reasoning, emotion and behavior, in order to anticipate possible misunderstandings due to differences in handling the same situation, and to try and resolve them. Artificial Intelligence, and more specifically, the field of Intelligent Systems design, aims at building systems that mimic the behavior of human beings in order to complete tasks more efficiently than humans could by themselves. Consequently, in the last decade, experts and scholars in the field of Intelligent Systems have been increasingly tackling the notion of cultural awareness. A Culturally-Aware Intelligent System can be defined as a system where Culture-related or, more generally, socio-cultural information is modeled and used to design the human-machine interface, or to provide support with the task carried out by the system, be it reasoning, simulation or any other task involving cultural knowledge.

Wie ein gefräßiges Ungeheuer verleibt sich die Digitalisierung Lebensbereich für Lebensbereich, Wirtschaftszweig für Wirtschaftszweig ein. Ein regelrechtes Datenzeitalter steht uns bevor. Die digitale Revolution ist nicht mehr aufzuhalten, und die nächste Stufe der digitalen Vernetzung ist bereits in vollem Gange. Das Internet der Dinge zieht aus den Labors in den Alltag der Konsumenten. Der neue'Homo connectus'lebt in einer schönen neuen Welt, die wie durch Geisterhand sich öffnende Türen und Fenster verspricht, die heimische Heizungsanlage steuert, die Einkaufsliste über die Lücken im Kühlschrank erstellt und die Großmutter beim Blick in den Spiegel daran erinnert, die Tablette für die Nacht einzunehmen. Die freundliche Stimme aus dem Lautsprecher, die auf alle Fragen eine Antwort weiß, auf Wunsch Musik spielt oder auch das Wetter am Urlaubsziel recherchiert, ist ein neues Familienmitglied. Doch sind erst einmal alle Geräte miteinander verbunden, bilden sie für den geschickten Hacker eine riesige Armee, mit deren Hilfe er den Sicherheitsapparat ganzer Weltmächte zusammenbrechen lassen kann. Die Sicherheit des Internets ist in Gefahr. Aus den kleinen Dingen, die das Leben angenehmer machen sollen, wird eine mächtige Cyberwaffe. Und die freundliche Stimme aus dem Lautsprecher hat all die Gespräche, auch wenn sie noch so intim waren, aufgezeichnet und ausgewertet: Der User begibt sich freiwillig in die absolute Kontrolle von Weltkonzernen. Dieses Buch hat nicht den Anspruch, die Zukunft vorauszusagen – was auch ziemlich vermessen wäre. Aber es soll helfen, in der nahen Zukunft einen vernünftigen und möglichst sicheren Umgang mit der digitalen Welt zu ermöglichen. Denn nur wenn man weiß, was hinter den Apps und Gadgets der smarten Welt steckt, was Daten wirklich bedeuten und wie wir uns durch schlaue Anwendungen schützen können, können wir uns selbstverständlich und furchtlos in ihr bewegen. Damit wird das Buch zu einem umfangreichen Praxisleitfaden für alle, die sich über das Leben in der digitalen Welt Gedanken machen.

This open access book examines the methodological complications of using complexity science concepts within the social science domain. The opening chapters take the reader on a tour through the development of simulation methodologies in the fields of artificial life and population biology, then demonstrates the growing popularity and relevance of these methods in the social sciences. Following an in-depth analysis of the potential impact of these methods on social science and social theory, the text provides substantive examples of the application of agent-based models in the field of demography. This work offers a unique combination of applied simulation work and substantive, in-depth philosophical analysis, and as such has potential appeal for specialist social scientists, complex systems scientists, and philosophers of science interested in the methodology of simulation and the practice of interdisciplinary computing research.​

Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success.This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems.Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. What You'll Learn Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for successDesign an intelligent user experience: Produce data to help make the Intelligent System better over timeImplement an Intelligent System: Execute, manage, and measure Intelligent Systems in practiceCreate intelligence: Use different approaches, including machine learningOrchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want Who This Book Is For Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems

Multimedia represents information in novel and varied formats. One of the most prevalent examples of continuous media is video. Extracting underlying data from these videos can be an arduous task. From video indexing, surveillance, and mining, complex computational applications are required to process this data. Intelligent Analysis of Multimedia Information is a pivotal reference source for the latest scholarly research on the implementation of innovative techniques to a broad spectrum of multimedia applications by presenting emerging methods in continuous media processing and manipulation. This book offers a fresh perspective for students and researchers of information technology, media professionals, and programmers.

One of the most actively growing subareas in multi-agent systems is computational social choice theory, which provides a theoretical foundation for preference aggregation and collective decision-making in multi-agent domains. It is concerned with the application of techniques developed in computer science, including complexity analysis and algorithm design, in the study of social choice mechanisms, such as voting. It seeks to import concepts from social choice theory into Artificial Intelligence and computing.People often have to reach a joint decision despite conflicting preferences over the alternatives. This joint decision can be reached by an informal negotiating process or by a carefully specified protocol. Over the course of the past decade or so, computer scientists have also become deeply involved in this study. Within computer science, there is a number of settings where a decision must be made based on the conflicting preferences of multiple parties. The paradigms of computer science give a different and useful perspective on some of the classic problems in economics and related disciplines.A natural and very general approach for deciding among multiple alternatives is to vote on them. Voting is one of the most popular ways of reaching common decisions. As such, the study of elections is an area where fields such as computer science, economics, business, operations research, and political science can be brought together. Social choice theory deals with voting scenarios, in which a set of individuals must select an outcome from a set of alternatives.This book focuses on convergence to pure strategy Nash equilibria in plurality voting games and a number of other positional and non-positional scoring rules. In such games, the voters strategically choose a candidate to vote for, and the winner is determined by the plurality (or other) voting rules. Voters take turns modifying their votes; these manipulations are classified according to the way in which they affect the outcome of the election. The focus is on achieving a stable outcome, taking strategic behaviour into account. A voting profile is in equilibrium, when no voter can change his vote so that his more preferable candidate gets elected. The book investigates restrictions on the number of iterations that can be made for different voting rules, considering both weighted and equi-weighted voting settings.

This book explores cognitive behavior among Internet of Things. Using a series of current and futuristic examples – appliances, personal assistants, robots, driverless cars, customer care, engineering, monetization, and many more – the book covers use cases, technology and communication aspects of how machines will support individuals and organizations. This book examines the Cognitive Things covering a number of important questions: • What are Cognitive Things? • What applications can be driven from Cognitive Things – today and tomorrow? • How will these Cognitive Things collaborate with each and other, with individuals and with organizations? • What is the cognitive era? How is it different from the automation era? • How will the Cognitive Things support or accelerate human problem solving? • Which technical components make up cognitive behavior? • How does it redistribute the work-load between humans and machines? • What types of data can be collected from them and shared with external organizations? • How do they recognize and authenticate authorized users? How is the data safeguarded from potential theft? Who owns the data and how are the data ownership rights enforced? Overall, Sathi explores ways in which Cognitive Things bring value to individuals as well as organizations and how to integrate the use of the devices into changing organizational structures. Case studies are used throughout to illustrate how innovators are already benefiting from the initial explosion of devices and data. Business executives, operational managers, and IT professionals will understand the fundamental changes required to fully benefit from cognitive technologies and howto utilize them for their own success.

The focus of this book is on three influential cognitive motives: achievement, affiliation, and power motivation. Incentive-based theories of achievement, affiliation and power motivation are the basis for competence-seeking behaviour, relationship-building, leadership, and resource-controlling behaviour in humans. In this book we show how these motives can be modelled and embedded in artificial agents to achieve behavioural diversity. Theoretical issues are addressed for representing and embedding computational models of motivation in rule-based agents, learning agents, crowds and evolution of motivated agents. Practical issues are addressed for defining games, mini-games or in-game scenarios for virtual worlds in which computer-controlled, motivated agents can participate alongside human players. The book is structured into four parts: game playing in virtual worlds by humans and agents; comparing human and artificial motives; game scenarios for motivated agents; and evolution and the future of motivated game-playing agents. It will provide game programmers, and those with an interest in artificial intelligence, with the knowledge required to develop diverse, believable game-playing agents for virtual worlds.

This book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the area of automated negotiation. It gives new practical and theoretical insights into the design and evaluation of automated negotiators. It describes an innovative negotiating agent framework that enables systematic exploration of the space of possible negotiation strategies by recombining different agent components. Using this framework, new and effective ways are formulated for an agent to learn, bid, and accept during a negotiation. The findings have been evaluated in four annual instantiations of the International Automated Negotiating Agents Competition (ANAC), the results of which are also outlined here. The book also describes several methodologies for evaluating and comparing negotiation strategies and components, with a special emphasis on performance and accuracy measures.

Will your next doctor be a human being—or a machine? Will you have a choice? If you do, what should you know before making it?This book introduces the reader to the pitfalls and promises of artificial intelligence (AI) in its modern incarnation and the growing trend of systems to'reach off the Web'into the real world. The convergence of AI, social networking, and modern computing is creating an historic inflection point in the partnership between human beings and machines with potentially profound impacts on the future not only of computing but of our world and species.AI experts and researchers James Hendler—co-originator of the Semantic Web (Web 3.0)—and Alice Mulvehill—developer of AI-based operational systems for DARPA, the Air Force, and NASA—explore the social implications of AI systems in the context of a close examination of the technologies that make them possible. The authors critically evaluate the utopian claims and dystopian counterclaimsof AI prognosticators. Social Machines: The Coming Collision of Artificial Intelligence, Social Networking, and Humanity is your richly illustrated field guide to the future of your machine-mediated relationships with other human beings and with increasingly intelligent machines.What Readers Will LearnWhat the concept of a social machine is and how the activities of non-programmers are contributing to machine intelligenceHow modern artificial intelligence technologies, such as Watson, are evolving and how they process knowledge from both carefully produced information (such as Wikipedia and journal articles) and from big data collectionsThe fundamentals of neuromorphic computing, knowledge graph search, and linked data, as well as the basic technology concepts that underlie networking applications such as Facebook and TwitterHow the change in attitudes towards cooperative work on the Web, especially in the younger demographic, is critical to the future of Web applicationsWho This Book Is ForGeneral readers and technically engaged developers, entrepreneurs, and technologists interested in the threats and promises of the accelerating convergence of artificial intelligence with social networks and mobile web technologies.

While the significance of networks in various human behavior and activities has a history as long as human's existence, network awareness is a recent scientific phenomenon. The neologism network science is just one or two decades old. Nevertheless, with this limited time, network thinking has substantially reshaped the recent development in economics, and almost all solutions to real-world problems involve the network element. This book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The authors begin with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling's segregation model and Axelrod's spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The text also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. It reviews a number of pioneering and representative models in this family. Upon the given foundation, the second part reviews three primary forms of network dynamics, such as diffusions, cascades, and influences. These primary dynamics are further extended and enriched by practical networks in goods-and-service markets, labor markets, and international trade. At the end, the book considers two challenging issues using agent-based models of networks: network risks and economic growth.

This book examines the use of agent-based modelling (ABM) in population studies, from concepts to applications, best practices to future developments. It features papers written by leading experts in the field that will help readers to better understand the usefulness of ABM for population projections, how ABM can be injected with empirical data to achieve a better match between model and reality, how geographic information can be fruitfully used in ABM, and how ABM results can be reported effectively and correctly.Coverage ranges from detailing the relation between ABM and existing paradigms in population studies to infusing agent-based models with empirical data. The papers show the benefits that ABM offers the field, including enhanced theory formation by better linking the micro level with the macro level, the ability to represent populations more adequately as complex systems, and the possibility to study rare events and the implications of alternative mechanisms in artificial laboratories.In addition, readers will discover guidelines and best practices with detailed examples of how to apply agent-based models in different areas of population research, including human mating behaviour, migration, and socio-structural determinants of health behaviours.Earlier versions of the papers in this book have been presented at the workshop “Recent Developments and Future Directions in Agent-Based Modelling in Population Studies,” which took place at the University of Leuven (KU Leuven), Belgium, in September 2014. The book will contribute to the development of best practices in the field and will provide a solid point of reference for scholars who want to start using agent-based modelling in their own research.

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.

From Facebook Messenger to Kik, and from Slack bots to Google Assistant, Amazon Alexa, and email bots, the new conversational apps are revolutionizing the way we interact with software. This practical guide shows you how to design and build great conversational experiences and delightful bots that help people be more productive, whether it's for a new consumer service or an enterprise efficiency product.Ideal for designers, product managers, and entrepreneurs, this book explores what works and what doesn't in real-world bot examples, and provides practical design patterns for your bot-building toolbox. You'll learn how to use an effective onboarding process, outline different flows, define a bot personality, and choose the right balance of rich control and text.Explore different bot use-cases and design best practicesUnderstand bot anatomy—such as brand and personality, conversations, advanced UI controls—and their associated design patternsLearn steps for building a Facebook Messenger consumer bot and a Slack business botExplore the lessons learned and shared experiences of designers and entrepreneurs who have built botsDesign and prototype your first bot, and experiment with user feedback

You don't need to be a wizard to transform a game you like into a game you love. Imagine if you could give your favorite PC game a more informative heads-up display or instantly collect all that loot from your latest epic battle.Bring your knowledge of Windows-based development and memory management, and Game Hacking will teach you what you need to become a true game hacker. Learn the basics, like reverse engineering, assembly code analysis, programmatic memory manipulation, and code injection, and hone your new skills with hands-on example code and practice binaries.Level up as you learn how to:–Scan and modify memory with Cheat Engine–Explore program structure and execution flow with OllyDbg–Log processes and pinpoint useful data files with Process Monitor–Manipulate control flow through NOPing, hooking, and more–Locate and dissect common game memory structuresYou'll even discover the secrets behind common game bots, including:–Extrasensory perception hacks, such as wallhacks and heads-up displays–Responsive hacks, such as autohealers and combo bots–Bots with artificial intelligence, such as cave walkers and automatic lootersGame hacking might seem like black magic, but it doesn't have to be. Once you understand how bots are made, you'll be better positioned to defend against them in your own games. Journey through the inner workings of PC games with Game Hacking, and leave with a deeper understanding of both game design and computer security.

This volume presents a collection of research studies on sophisticated and functional computational instruments able to recognize, process, and store relevant situated interactional signals, as well as, interact with people, displaying reactions (under conditions of limited time) that show abilities of appropriately sensing and understanding environmental changes, producing suitable, autonomous, and adaptable responses to various social situations. These social robotic autonomous systems will improve the quality of life of their end-users while assisting them on several needs, ranging from educational settings, health care assistance, communicative disorders, and any disorder impairing either their physical, cognitive, or social functional activities. The multidisciplinary themes presented in the volume will be interesting for experts and students coming from different research fields and with different knowledge and backgrounds. The research reported is particularly relevant for academic centers, and Research & Development Institutions.

This book focuses on automated negotiations based on multi-agent systems. It is intended for researchers and students in various fields involving autonomous agents and multi-agent systems, such as e-commerce tools, decision-making and negotiation support systems, and collaboration tools. The contents will help them to understand the concept of automated negotiations, negotiation protocols, negotiating agents'strategies, and the applications of those strategies. In this book, some negotiation protocols focusing on the multiple interdependent issues in negotiations are presented, making it possible to find high-quality solutions for the complex agents'utility functions. This book is a compilation of the extended versions of the very best papers selected from the many that were presented at the International Workshop on Agent-Based Complex Automated Negotiations.

This book presents new approaches that advance research in all aspects of agent-based models, technologies, simulations and implementations for data intensive applications. The nine chapters contain a review of recent cross-disciplinary approaches in cloud environments and multi-agent systems, and important formulations of data intensive problems in distributed computational environments together with the presentation of new agent-based tools to handle those problems and Big Data in general.This volume can serve as a reference for students, researchers and industry practitioners working in or interested in joining interdisciplinary work in the areas of data intensive computing and Big Data systems using emergent large-scale distributed computing paradigms. It will also allow newcomers to grasp key concepts and potential solutions on advanced topics of theory, models, technologies, system architectures and implementation of applications in Multi-Agent systems and data intensive computing.

Industrial Agents explains how multi-agent systems improve collaborative networks to offer dynamic service changes, customization, improved quality and reliability, and flexible infrastructure. Learn how these platforms can offer distributed intelligent management and control functions with communication, cooperation and synchronization capabilities, and also provide for the behavior specifications of the smart components of the system. The book offers not only an introduction to industrial agents, but also clarifies and positions the vision, on-going efforts, example applications, assessment and roadmap applicable to multiple industries. This edited work is guided and co-authored by leaders of the IEEE Technical Committee on Industrial Agents who represent both academic and industry perspectives and share the latest research along with their hands-on experiences prototyping and deploying industrial agents in industrial scenarios. - Learn how new scientific approaches and technologies aggregate resources such next generation intelligent systems, manual workplaces and information and material flow system - Gain insight from experts presenting the latest academic and industry research on multi-agent systems - Explore multiple case studies and example applications showing industrial agents in a variety of scenarios - Understand implementations across the enterprise, from low-level control systems to autonomous and collaborative management units

Según los reales decretos que afectan al desarrollo de esta obra, es imprescindible que el desarrollo docente de la misma sea lo más práctico posible. A lo largo de la lectura, el lector descubrirá gran cantidad de conceptos relacionados con la administración de servicios web y los fundamentos prácticos que nos indicarán cómo llevarla a cabo. Además, al final de cada capítulo podrá encontrar una serie de preguntas test que nos ayudarán a afianzar los conceptos aprendidos a nivel teórico y práctico. Las respuestas a los diferentes test se podrán encontrar recopiladas al final de la obra. Durante todo el proceso de redacción se ha tenido en cuenta a los sistemas operativos Microsoft Windows y GNU/Linux centrándonos en las distribuciones Ubuntu y Fedora por su amplia presencia entre los usuarios de este sistema operativo, así como la compatibilidad de los programas planteados en ambos sistemas operativos.

The amount of data used in the business world has been growing at a rapid and exponential rate. These large volumes of data have led not only to the rise of big data analytics, but to the need for improvements and advancements in the management of it. Recent Advances in Intelligent Technologies and Information Systems brings together current practices and innovations in the management and processing of diverse big data sets through technological integration. Focusing on concepts such as semantic technologies, open source tools, and soft computing, this book is an integral reference source for professionals, researchers, and practitioners interested in the application of technological advancements.