As the videogame industry has grown up, the need for better stories and characters has dramatically increased, yet traditional screenwriting techniques alone cannot equip writers for the unique challenges of writing stories where the actions and decisions of a diverse range of players are at the centre of every narrative experience. Game Writing: Narrative Skills for Videogames was the first book to demystify the emerging field of game writing by identifying and explaining the skills required for creating videogame narrative. Through the insights and experiences of professional game writers, this revised edition captures a snapshot of the narrative skills employed in today's game industry and presents them as practical articles accompanied by exercises for developing the skills discussed. The book carefully explains the foundations of the craft of game writing, detailing all aspects of the process from the basics of narrative to guiding the player and the challenges of nonlinear storytelling. Throughout the book there is a strong emphasis on the skills developers and publishers expect game writers to know. This second edition brings the material up to date and adds four new chapters covering MMOs, script formats, narrative design for urban games, and new ways to think about videogame narrative as an art form. Suitable for both beginners and experienced writers, Game Writing is the essential guide to all the techniques of game writing. There's no better starting point for someone wishing to get into this exciting field, whether they are new game writers wishing to hone their skills, or screenwriters hoping to transfer their skills to the games industry.

Intelligence Science: Leading the Age of Intelligence covers the emerging scientific research on the theory and technology of intelligence, bringing together disciplines such as neuroscience, cognitive science, and artificial intelligence to study the nature of intelligence, the functional simulation of intelligent behavior, and the development of new intelligent technologies. The book presents this complex, interdisciplinary area of study in an accessible volume, introducing foundational concepts and methods, and presenting the latest trends and developments. Chapters cover the Foundations of neurophysiology, Neural computing, Mind models, Perceptual intelligence, Language cognition, Learning, Memory, Thought, Intellectual development and cognitive structure, Emotion and affect, and more. This volume synthesizes a very rich and complex area of research, with an aim of stimulating new lines of enquiry.

The technology of Artificial Intelligence is here, and moving fast, without ethical standards in place. A Blueprint for the Regulation of Artificial Intelligence Technologies leans on classical western philosophy for its ethical grounding. Values such as conscience, rights, equity, and discrimination, establish a basis for regulatory standards. Multiple international agencies with governing interests are compared. The development of ethical standards is suggested through two new non-governmental organizations (NGOs). The first is to develop standards that evolve from practice, while the second acts as an ombudsman to settle abuse. Both NGOs are envisioned to cooperate with regulators. More than seeking a perfect solution, the book aims to balance the tension between conflicting interests, with the goal to keep this dangerously wonderful technology under global human control. For that to materialize, the technology needs to have a seat on the table of global ethics. The final chapter lists fourteen thinking points to achieve an ethics balance for new technologies.

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more.

Quantitative Atomic-Resolution Electron Microscopy, Volume 217, the latest release in the Advances in Imaging and Electron Physics series merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods. Chapters in this release include Statistical parameter estimation theory, Efficient fitting algorithm, Statistics-based atom counting , Atom column detection, Optimal experiment design for nanoparticle atom-counting from ADF STEM images, and more.

Introduction to Chemical Engineering Analysis Using Mathematica, Second Edition reviews the processes and designs used to manufacture, use, and dispose of chemical products using Mathematica, one of the most powerful mathematical software tools available for symbolic, numerical, and graphical computing. Analysis and computation are explained simultaneously. The book covers the core concepts of chemical engineering, ranging from the conservation of mass and energy to chemical kinetics. The text also shows how to use the latest version of Mathematica, from the basics of writing a few lines of code through developing entire analysis programs. This second edition has been fully revised and updated, and includes analyses of the conservation of energy, whereas the first edition focused on the conservation of mass and ordinary differential equations.

Businesses have had to face many challenges due to the COVID-19 pandemic; to survive in the changing landscape, they had to adapt quickly and implement new tactics and best practices to stay competitive. Networking is one of the many areas that looks vastly different in a post-pandemic world and companies must understand this change or risk falling behind. Further study is required to uncover the various difficulties and potential future directions of networking and innovation within the business landscape. The Handbook of Research on Digital Innovation and Networking in Post-COVID-19 Organizations provides a thorough overview of the ways in which organizations have had to change and adapt to the new business environments and considers how networking looks different in a post-COVID-19 world. Covering key topics such as organizational structures, consumer behavior, teleworking, and collaborations, this major reference work is ideal for managers, business owners, industry professionals, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.

This book examines the tangled responsibilities of states, companies, and individuals surrounding human rights in the digital age. Digital technologies have a huge impact – for better and worse – on human lives; while they can clearly enhance some human rights, they also facilitate a wide range of violations. States are expected to implement efficient measures against powerful private companies, but, at the same time, they are drawn to technologies that extend their own control over citizens. Tech companies are increasingly asked to prevent violations committed online by their users, yet many of their business models depend on the accumulation and exploitation of users’ personal data. While civil society has a crucial part to play in upholding human rights, it is also the case that individuals harm other individuals online. All three stakeholders need to ensure that technology does not provoke the disintegration of human rights. Bringing together experts from a range of disciplines, including law, international relations, and journalism, this book provides a detailed analysis of the impact of digital technologies on human rights, which will be of interest to academics, research students and professionals concerned by this issue.

Machine reading comprehension (MRC) is a cutting-edge technology in natural language processing (NLP). MRC has recently advanced significantly, surpassing human parity in several public datasets. It has also been widely deployed by industry in search engine and quality assurance systems. Machine Reading Comprehension: Algorithms and Practice performs a deep-dive into MRC, offering a resource on the complex tasks this technology involves. The title presents the fundamentals of NLP and deep learning, before introducing the task, models, and applications of MRC. This volume gives theoretical treatment to solutions and gives detailed analysis of code, and considers applications in real-world industry. The book includes basic concepts, tasks, datasets, NLP tools, deep learning models and architecture, and insight from hands-on experience. In addition, the title presents the latest advances from the past two years of research. Structured into three sections and eight chapters, this book presents the basis of MRC; MRC models; and hands-on issues in application. This book offers a comprehensive solution for researchers in industry and academia who are looking to understand and deploy machine reading comprehension within natural language processing.

The Destiny Grimoire Anthology is a must-have collectible lore compendium assembled for Destiny's devoted and enlightened scholars and lore lovers, as well as fans of fantasy and science fiction storytelling. The Destiny Grimoire Anthology weaves tales from multiple sources together for the first time, casting new light on Destiny's most legendary heroes, infamous villains, and their greatest moments of triumph and tragedy.

The advent of connected, smart technologies for the built environment may promise a significant value that has to be reached to develop digital city models. At the international level, the role of digital twin is strictly related to massive amounts of data that need to be processed, which proposes several challenges in terms of digital technologies capability, computing, interoperability, simulation, calibration, and representation. In these terms, the development of 3D parametric models as digital twins to evaluate energy assessment of private and public buildings is considered one of the main challenges of the last years. The ability to gather, manage, and communicate contents related to energy saving in buildings for the development of smart cities must be considered a specificity in the age of connection to increase citizen awareness of these fields. The Handbook of Research on Developing Smart Cities Based on Digital Twins contains in-depth research focused on the description of methods, processes, and tools that can be adopted to achieve smart city goals. The book presents a valid medium for disseminating innovative data management methods related to smart city topics. While highlighting topics such as data visualization, a web-based ICT platform, and data-sharing methods, this book is ideally intended for researchers in the building industry, energy, and computer science fields; public administrators; building managers; and energy professionals along with practitioners, stakeholders, researchers, academicians, and students interested in the implementation of smart technologies for the built environment.

Advances in digital technologies continue to impact all areas of life, including the business sector. Digital transformation is ascertained to usher in the digitalized economy and involves new concepts and management tools that must be considered in the context of management science and practice. For business leaders to ensure their companies remain competitive and relevant, it is essential for them to utilize these innovative technologies and strategies. The Handbook of Research on Digital Transformation Management and Tools highlights new digital concepts within management, such as digitalization and digital disruption, and addresses the paradigm shift in management science incurred by the digital transformation towards the digitalized economy. Covering a range of important topics such as cultural economy, online consumer behavior, sustainability, and social media, this major reference work is crucial for managers, business owners, researchers, scholars, academicians, practitioners, instructors, and students.