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  1. Games and rules : game mechanics for the 'magic circle'

    Bielefeld : Transcript, 2018

    Why do we play games and why do we play them on computers? The contributors of Games and Rules take a closer look at the core of each game and the motivational system that is the game mechanics. Games are control circuits that organize the game world with their (joint) players and establish motivations in a dedicated space, a Magic Circle , whereas game mechanics are constructs of rules designed for interactions that provide gameplay. Those rules form the base for all the excitement and frustration we experience in games. This anthology contains individual essays by authors with backgrounds in Game Design and Game Studies, who lead the discourse to get to the bottom of game mechanics in video games and the real worldWhy do we play games and why do we play them on computers? The contributors of Games and Rules take a closer look at the core of each game and the motivational system that is the game mechanics. Games are control circuits that organize the game world with their (joint) players and establish motivations in a dedicated space, a "Magic Circle, " whereas game mechanics are constructs of rules designed for interactions that provide gameplay. Those rules form the base for all the excitement and frustration we experience in games. This anthology contains individual essays by authors with backgrounds in game design and game studies, who lead the discourse to get to the bottom of game mechanics in video games and the real world.

    Online www.oapen.org

  2. AI for behavioural science

    Mills, Stuart (Economist)
    Boca Raton : CRC Press, 2022.

    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.

    Online Safari Books Online

  3. MACHINE LEARNING IN MEDICINE [electronic resource]

    BOCA RATON : CHAPMAN & HALL CRC, 2021

    Machine Learning in Medicine covers the state-of-the-art techniques of machine learning and their applications in the medical field. It presents several computer-aided diagnosis (CAD) systems, which have played an important role in the diagnosis of several diseases in the past decade, e.g., cancer detection, resulting in the development of several successful systems. New developments in machine learning may make it possible in the near future to develop machines that are capable of completely performing tasks that currently cannot be completed without human aid, especially in the medical field. This book covers such machines, including convolutional neural networks (CNNs) with different activation functions for small- to medium-size biomedical datasets, detection of abnormal activities stemming from cognitive decline, thermal dose modelling for thermal ablative cancer treatments, dermatological machine learning clinical decision support systems, artificial intelligence-powered ultrasound for diagnosis, practical challenges with possible solutions for machine learning in medical imaging, epilepsy diagnosis from structural MRI, Alzheimer's disease diagnosis, classification of left ventricular hypertrophy, and intelligent medical language understanding. This book will help to advance scientific research within the broad field of machine learning in the medical field. It focuses on major trends and challenges in this area and presents work aimed at identifying new techniques and their use in biomedical analysis, including extensive references at the end of each chapterProvides a comprehensive overview of machine learning and deep learning techniques for biomedical imaging Includes thoracic imaging, abdominal imaging, brain imaging, and retinal imaging Covers new and emerging methods in machine learning Features contributions from leading experts Presents tools to improve computer aided diagnosis.

    Online Taylor & Francis eBooks

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