This book is a concise introduction to emerging concepts and ideas found at the intersection of contemporary behavioural science and artificial intelligence. The book explores how these disciplines interact, change, and adapt to one another and what the implications of such an interaction are for practice and society. AI for Behavioural Science book begins by exploring the field of machine behaviour, which advocates using behavioural science to investigate artificial intelligence. This perspective is built upon to develop a framework of terminology that treats humans and machines as comparable entities possessing their own motive power. From here, the notion of artificial intelligence systems becoming choice architects is explored through a series of reconceptualisations. The architecting of choices is reconceptualised as a process of selection from a set of choice architectural designs, while human behaviour is reconceptualised in terms of probabilistic outcomes. The material difference between the so-called "manual nudging" and "automatic nudging" (or hypernudging) is then explored. The book concludes with a discussion of who is responsible for autonomous choice architects.

Artificial Intelligence in Behavioral and Mental Health Care summarizes recent advances in artificial intelligence as it applies to mental health clinical practice. Each chapter provides a technical description of the advance, review of application in clinical practice, and empirical data on clinical efficacy. In addition, each chapter includes a discussion of practical issues in clinical settings, ethical considerations, and limitations of use. The book encompasses AI based advances in decision-making, in assessment and treatment, in providing education to clients, robot assisted task completion, and the use of AI for research and data gathering. This book will be of use to mental health practitioners interested in learning about, or incorporating AI advances into their practice and for researchers interested in a comprehensive review of these advances in one source. - Summarizes AI advances for use in mental health practice - Includes advances in AI based decision-making and consultation - Describes AI applications for assessment and treatment - Details AI advances in robots for clinical settings - Provides empirical data on clinical efficacy - Explores practical issues of use in clinical settings

Human behavior is never an exact science, making the design and programming of artificial intelligence that seeks to replicate human behavior difficult. Usually, the answers cannot be found in sterile algorithms that are often the focus of artificial intelligence programming. However, by analyzing why people behave the way we do, we can break down the process into increasingly smaller components. We can model many of those individual components in the language of logic and mathematics and then reassemble them into larger, more involved decision-making processes. Drawing from classical game theory, "Behavioral Mathematics for Game AI" covers both the psychological foundations of human decisions and the mathematical modeling techniques that AI designers and programmers can use to replicate them. With examples from both real life and game situations, you'll explore topics such as utility, the fallacy of rational behavior, and the inconsistencies and contradictions that human behavior often exhibits. You'll examine various ways of using statistics, formulas, and algorithms to create believable simulations and to model these dynamic, realistic, and interesting behaviors in video games. Finally, you'll be introduced to a number of tools you can use in conjunction with standard AI algorithms to make it easier to utilize the mathematical models.

"Artificial Intelligence for Behavioural Science is a concise introduction to emerging concepts and ideas found at the intersection of contemporary behavioural science and artificial intelligence. The book explores how these disciplines interact, change and adapt to one another, and what the implications of such an interaction are for practice and society. The book begins by exploring the field of machine behaviour, which advocates using behavioural science to investigate artificial intelligence. This perspective is built upon to develop a framework of terminology which treats humans and machines as comparable entities possessive of their own motive power. From here, the notion of artificial intelligence systems becoming choice architects is explored through a series of reconceptualisations. The architecting of choices is reconceptualised as a process of selection from a set of choice architectural designs, while human behaviour is reconceptualised in terms of probabilistic outcomes. The material difference between so-called 'manual nudging' and 'automatic nudging' (or hypernudging) is then explored. The book concludes with a discussion of who is responsible for autonomous choice architects. Stuart Mills is a behavioural economist with a background in economics and political economy. His research focuses on nudge theory, personalisation, and digital economy. He is interested in the intersection of technology, data and behavioural science within public policy and finance, as well as the wider political economy implications"--

Intelligent agents are employed as the central characters in this introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. A distinguishing feature of this text is in its evolutionary approach to the study of AI. This book provides a refreshing and motivating synthesis of the field by one of AI's master expositors and leading researches. - An evolutionary approach provides a unifying theme - Thorough coverage of important AI ideas, old and new - Frequent use of examples and illustrative diagrams - Extensive coverage of machine learning methods throughout the text - Citations to over 500 references - Comprehensive index

Kizzi Talks about Behavioural Science in Marketing is a groundbreaking book that empowers marketing professionals to harness the power of Behavioural Science and revolutionize their marketing strategies. In this highly informative and inspiring guide, Kizzi, creator Business Game Changer Magazine, explores the vast potential of incorporating Behavioural Science principles into the realm of marketing. Written in a clear and accessible style, this book is tailored specifically for marketing professionals who are seeking to enhance their understanding of human behavior and leverage it to drive impactful marketing campaigns. Unlike other technical texts, Kizzi Talks about Behavioural Science in Marketing presents complex concepts without unnecessary jargon, making it a valuable resource for marketers at any level of expertise. With an unwavering focus on practical application, the book delves into the core scientific principles that underpin Behavioural Science, providing concrete examples from the business world. Readers will gain insights into key concepts such as social proof, cognitive biases, decision-making processes, and emotional triggers, and how these principles can be integrated seamlessly into marketing strategies. Through captivating stories, relatable anecdotes, and real-world case studies, Kizzi illuminates the transformative potential of Behavioural Science in marketing. Readers will learn how to craft compelling narratives, design persuasive messaging, optimize customer experiences, and drive consumer behavior in ways that resonate deeply with their target audience.

This book aims to facilitate the task of reviewing and selecting relevant theories to inform the design of behaviour change interventions and policies. The main goal is to provide on accessible source of potentially useful theories from a range of disciplines beyond those usually considered. It also provides on opportunity to analyse brood issues around the use of theory in the design of behaviour change interventions and examine areas where there is scope for improvement.