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Author: Sebastian Loth Publisher: Frontiers Media SA ISBN: 2889198456 Category : Human-robot interaction Languages : en Pages : 143
Book Description
Powerful and economic sensors such as high definition cameras and corresponding recognition software have become readily available, e.g. for face and motion recognition. However, designing user interfaces for robots, phones and computers that facilitate a seamless, intuitive, and apparently effortless communication as between humans is still highly challenging. This has shifted the focus from developing ever faster and higher resolution sensors to interpreting available sensor data for understanding social signals and recognising users' intentions. Psychologists, Ethnologists, Linguists and Sociologists have investigated social behaviour in human-human interaction. But their findings are rarely applied in the human-robot interaction domain. Instead, robot designers tend to rely on either proof-of-concept or machine learning based methods. In proving the concept, developers effectively demonstrate that users are able to adapt to robots deployed in the public space. Typically, an initial period of collecting human-robot interaction data is used for identifying frequently occurring problems. These are then addressed by adjusting the interaction policies on the basis of the collected data. However, the updated policies are strongly biased by the initial design of the robot and might not reflect natural, spontaneous user behaviour. In the machine learning approach, learning algorithms are used for finding a mapping between the sensor data space and a hypothesised or estimated set of intentions. However, this brute-force approach ignores the possibility that some signals or modalities are superfluous or even disruptive in intention recognition. Furthermore, this method is very sensitive to peculiarities of the training data. In sum, both methods cannot reliably support natural interaction as they crucially depend on an accurate model of human intention recognition. Therefore, approaches to social robotics from engineers and computer scientists urgently have to be informed by studies of intention recognition in natural human-human communication. Combining the investigation of natural human behaviour and the design of computer and robot interfaces can significantly improve the usability of modern technology. For example, robots will be easier to use by a broad public if they can interpret the social signals that users spontaneously produce for conveying their intentions anyway. By correctly identifying and even anticipating the user's intention, the user will perceive that the system truly understands her/his needs. Vice versa, if a robot produces socially appropriate signals, it will be easier for its users to understand the robot's intentions. Furthermore, studying natural behaviour as a basis for controlling robots and other devices results in greater robustness, responsiveness and approachability. Thus, we welcome submissions that (a) investigate how relevant social signals can be identified in human behaviour, (b) investigate the meaning of social signals in a specific context or task, (c) identify the minimal set of intentions for describing a context or task, (d) demonstrate how insights from the analysis of social behaviour can improve a robot's capabilities, or (e) demonstrate how a robot can make itself more understandable to the user by producing more human-like social signals.
Author: Sebastian Loth Publisher: Frontiers Media SA ISBN: 2889198456 Category : Human-robot interaction Languages : en Pages : 143
Book Description
Powerful and economic sensors such as high definition cameras and corresponding recognition software have become readily available, e.g. for face and motion recognition. However, designing user interfaces for robots, phones and computers that facilitate a seamless, intuitive, and apparently effortless communication as between humans is still highly challenging. This has shifted the focus from developing ever faster and higher resolution sensors to interpreting available sensor data for understanding social signals and recognising users' intentions. Psychologists, Ethnologists, Linguists and Sociologists have investigated social behaviour in human-human interaction. But their findings are rarely applied in the human-robot interaction domain. Instead, robot designers tend to rely on either proof-of-concept or machine learning based methods. In proving the concept, developers effectively demonstrate that users are able to adapt to robots deployed in the public space. Typically, an initial period of collecting human-robot interaction data is used for identifying frequently occurring problems. These are then addressed by adjusting the interaction policies on the basis of the collected data. However, the updated policies are strongly biased by the initial design of the robot and might not reflect natural, spontaneous user behaviour. In the machine learning approach, learning algorithms are used for finding a mapping between the sensor data space and a hypothesised or estimated set of intentions. However, this brute-force approach ignores the possibility that some signals or modalities are superfluous or even disruptive in intention recognition. Furthermore, this method is very sensitive to peculiarities of the training data. In sum, both methods cannot reliably support natural interaction as they crucially depend on an accurate model of human intention recognition. Therefore, approaches to social robotics from engineers and computer scientists urgently have to be informed by studies of intention recognition in natural human-human communication. Combining the investigation of natural human behaviour and the design of computer and robot interfaces can significantly improve the usability of modern technology. For example, robots will be easier to use by a broad public if they can interpret the social signals that users spontaneously produce for conveying their intentions anyway. By correctly identifying and even anticipating the user's intention, the user will perceive that the system truly understands her/his needs. Vice versa, if a robot produces socially appropriate signals, it will be easier for its users to understand the robot's intentions. Furthermore, studying natural behaviour as a basis for controlling robots and other devices results in greater robustness, responsiveness and approachability. Thus, we welcome submissions that (a) investigate how relevant social signals can be identified in human behaviour, (b) investigate the meaning of social signals in a specific context or task, (c) identify the minimal set of intentions for describing a context or task, (d) demonstrate how insights from the analysis of social behaviour can improve a robot's capabilities, or (e) demonstrate how a robot can make itself more understandable to the user by producing more human-like social signals.
Author: Alex Pentland Publisher: MIT Press ISBN: 0262261049 Category : Psychology Languages : en Pages : 205
Book Description
How understanding the signaling within social networks can change the way we make decisions, work with others, and manage organizations. How can you know when someone is bluffing? Paying attention? Genuinely interested? The answer, writes Alex Pentland in Honest Signals, is that subtle patterns in how we interact with other people reveal our attitudes toward them. These unconscious social signals are not just a back channel or a complement to our conscious language; they form a separate communication network. Biologically based “honest signaling,” evolved from ancient primate signaling mechanisms, offers an unmatched window into our intentions, goals, and values. If we understand this ancient channel of communication, Pentland claims, we can accurately predict the outcomes of situations ranging from job interviews to first dates. Pentland, an MIT professor, has used a specially designed digital sensor worn like an ID badge—a “sociometer”—to monitor and analyze the back-and-forth patterns of signaling among groups of people. He and his researchers found that this second channel of communication, revolving not around words but around social relations, profoundly influences major decisions in our lives—even though we are largely unaware of it. Pentland presents the scientific background necessary for understanding this form of communication, applies it to examples of group behavior in real organizations, and shows how by “reading” our social networks we can become more successful at pitching an idea, getting a job, or closing a deal. Using this “network intelligence” theory of social signaling, Pentland describes how we can harness the intelligence of our social network to become better managers, workers, and communicators.
Author: Rafael A. Calvo Publisher: Oxford Library of Psychology ISBN: 0199942234 Category : Computers Languages : en Pages : 625
Book Description
"The Oxford Handbook of Affective Computing is a definitive reference in the burgeoning field of affective computing (AC), a multidisciplinary field encompassing computer science, engineering, psychology, education, neuroscience, and other disciplines. AC research explores how affective factors influence interactions between humans and technology, how affect sensing and affect generation techniques can inform our understanding of human affect, and on the design, implementation, and evaluation of systems involving affect at their core. The volume features 41 chapters and is divided into five sections: history and theory, detection, generation, methodologies, and applications. Section 1 begins with the making of AC and a historical review of the science of emotion. The following chapters discuss the theoretical underpinnings of AC from an interdisciplinary viewpoint. Section 2 examines affect detection or recognition, a commonly investigated area. Section 3 focuses on aspects of affect generation, including the synthesis of emotion and its expression via facial features, speech, postures, and gestures. Cultural issues are also discussed. Section 4 focuses on methodological issues in AC research, including data collection techniques, multimodal affect databases, formats for the representation of emotion, crowdsourcing techniques, machine learning approaches, affect elicitation techniques, useful AC tools, and ethical issues. Finally, Section 5 highlights applications of AC in such domains as formal and informal learning, games, robotics, virtual reality, autism research, health care, cyberpsychology, music, deception, reflective writing, and cyberpsychology. This compendium will prove suitable for use as a textbook and serve as a valuable resource for everyone with an interest in AC."--
Author: Judee K. Burgoon Publisher: Cambridge University Press ISBN: 1108124585 Category : Computers Languages : en Pages : 441
Book Description
Social Signal Processing is the first book to cover all aspects of the modeling, automated detection, analysis, and synthesis of nonverbal behavior in human-human and human-machine interactions. Authoritative surveys address conceptual foundations, machine analysis and synthesis of social signal processing, and applications. Foundational topics include affect perception and interpersonal coordination in communication; later chapters cover technologies for automatic detection and understanding such as computational paralinguistics and facial expression analysis and for the generation of artificial social signals such as social robots and artificial agents. The final section covers a broad spectrum of applications based on social signal processing in healthcare, deception detection, and digital cities, including detection of developmental diseases and analysis of small groups. Each chapter offers a basic introduction to its topic, accessible to students and other newcomers, and then outlines challenges and future perspectives for the benefit of experienced researchers and practitioners in the field.
Author: Bruno Brochet Publisher: Springer ISBN: 3319184644 Category : Medical Languages : en Pages : 281
Book Description
This book is an up-to-date, comprehensive review of the neuropsychiatry of multiple sclerosis and related diseases, by active authorities in the field, with an emphasis on diagnosis and management. Critical appraisal of the methodological aspects and limitations of the current research on the neuropsychiatry of demyelinating diseases is included, and unanswered questions are highlighted. Pharmacological aspects of management are discussed. Neuropsychiatric Symptoms of Inflammatory Demyelinating Diseases is aimed at neurologists, multiple sclerosis specialists and psychiatrists, and will also be of interest to intensive care doctors, psychologists ad neuropsychologists, research and specialist nurses, clinical researchers and methodologists.
Author: Ulrich Pfeiffer Publisher: Frontiers E-books ISBN: 2889191044 Category : Languages : en Pages : 587
Book Description
The burgeoning field of social neuroscience has begun to illuminate the complex biological bases of human social cognitive abilities. However, in spite of being based on the premise of investigating the neural bases of interacting minds, the majority of studies have focused on studying brains in isolation using paradigms that investigate offline social cognition, i.e. social cognition from a detached observer's point of view, asking study participants to read out the mental states of others without being engaged in interaction with them. Consequently, the neural correlates of real-time social interaction have remained elusive and may —paradoxically— represent the 'dark matter' of social neuroscience. More recently, a growing number of researchers have begun to study online social cognition, i.e. social cognition from a participant's point of view, based on the assumption that there is something fundamentally different when we are actively engaged with others in real-time social interaction as compared to when we merely observe them. Whereas, for offline social cognition, interaction and feedback are merely a way of gathering data about the other person that feeds into processing algorithms 'inside’ the agent, it has been proposed that in online social cognition the knowledge of the other —at least in part— resides in the interaction dynamics ‘between’ the agents. Furthermore being a participant in an ongoing interaction may entail a commitment toward being responsive created by important differences in the motivational foundations of online and offline social cognition. In order to promote the development of the neuroscientific investigation of online social cognition, this Frontiers Research Topic aims at bringing together contributions from researchers in social neuroscience and related fields, whose work involves the study of at least two individuals and sometimes two brains, rather than single individuals and brains responding to a social context. Specifically, this Research Topic will adopt an interdisciplinary perspective on what it is that separates online from offline social cognition and the putative differences in the recruitment of underlying processes and mechanisms. Here, an important focal point will be to address the various roles of social interaction in contributing to and —at times— constituting our awareness of other minds. For this Research Topic, we, therefore, solicit reviews, original research articles, opinion and method papers, which address the investigation of social interaction and go beyond traditional concepts and ways of experimentation in doing so. While focusing on work in the neurosciences, this Research Topic also welcomes contributions in the form of behavioral studies, psychophysiological investigations, methodological innovations, computational approaches, developmental and patient studies. By focusing on cutting-edge research in social neuroscience and related fields, this Frontiers Research Topic will create new insights concerning the neurobiology of social interaction and holds the promise of helping social neuroscience to really go social.
Author: Patricia J. Bauer Publisher: Academic Press ISBN: 0080922627 Category : Psychology Languages : en Pages : 322
Book Description
Volume 37 of the Advances in Child Development and Behavior series includes 8 chapters that highlight some of the most recent research in developmental and educational psychology. A wide array of topics are discussed in detail, including the role of dyadic communication in infant social-cognitive development; space, number and the atypically developing brain; development from a behavioral genetics perspective; nonhuman primate studies of individual differences in pathways of lifespan development; the development of autobiographical memory: origins and consequences; the maturation of cognitive control and the adolescent brain; the developmental origin of naïve psychology; and children’s reasoning about traits. Each chapter provides in-depth discussions of various developmental psychology specializations. This volume serves as an invaluable resource for psychology researchers and advanced psychology students. Goes in depth to address 10 different developmental and educational psychology topics A necessary resource for both psychology researchers and students
Author: Vicki Anderson Publisher: Guilford Press ISBN: 1462504663 Category : Psychology Languages : en Pages : 422
Book Description
Synthesizing cutting-edge knowledge from multiple disciplines, this book explores the impact of acquired brain injury and developmental disabilities on children's emerging social skills. The editors present an innovative framework for understanding how brain processes interact with social development in both typically developing children and clinical populations. Key issues in assessment are addressed, including ways to measure both social function and brain function using developmentally sound tools. Balancing theoretical and clinical concerns, the book describes promising interventions for promoting children's adjustment and helping them participate more fully in the social world. Illustrations include six color plates.
Author: Jean-Claude Dreher Publisher: Academic Press ISBN: 0128053313 Category : Medical Languages : en Pages : 442
Book Description
Decision Neuroscience addresses fundamental questions about how the brain makes perceptual, value-based, and more complex decisions in non-social and social contexts. This book presents compelling neuroimaging, electrophysiological, lesional, and neurocomputational models in combination with hormonal and genetic approaches, which have led to a clearer understanding of the neural mechanisms behind how the brain makes decisions. The five parts of the book address distinct but inter-related topics and are designed to serve both as classroom introductions to major subareas in decision neuroscience and as advanced syntheses of all that has been accomplished in the last decade. Part I is devoted to anatomical, neurophysiological, pharmacological, and optogenetics animal studies on reinforcement-guided decision making, such as the representation of instructions, expectations, and outcomes; the updating of action values; and the evaluation process guiding choices between prospective rewards. Part II covers the topic of the neural representations of motivation, perceptual decision making, and value-based decision making in humans, combining neurcomputational models and brain imaging studies. Part III focuses on the rapidly developing field of social decision neuroscience, integrating recent mechanistic understanding of social decisions in both non-human primates and humans. Part IV covers clinical aspects involving disorders of decision making that link together basic research areas including systems, cognitive, and clinical neuroscience; this part examines dysfunctions of decision making in neurological and psychiatric disorders, such as Parkinson's disease, schizophrenia, behavioral addictions, and focal brain lesions. Part V focuses on the roles of various hormones (cortisol, oxytocin, ghrelin/leptine) and genes that underlie inter-individual differences observed with stress, food choices, and social decision-making processes. The volume is essential reading for anyone interested in decision making neuroscience. With contributions that are forward-looking assessments of the current and future issues faced by researchers, Decision Neuroscience is essential reading for anyone interested in decision-making neuroscience. - Provides comprehensive coverage of approaches to studying individual and social decision neuroscience, including primate neurophysiology, brain imaging in healthy humans and in various disorders, and genetic and hormonal influences on decision making - Covers multiple levels of analysis, from molecular mechanisms to neural-systems dynamics and computational models of how we make choices - Discusses clinical implications of process dysfunctions, including schizophrenia, Parkinson's disease, eating disorders, drug addiction, and pathological gambling - Features chapters from top international researchers in the field and full-color presentation throughout with numerous illustrations to highlight key concepts
Author: Sebastian Loth
Author: Sebastian Loth
Author: Alex Pentland
Author: Rafael A. Calvo
Author: Judee K. Burgoon
Author: Bennett, Paul
Author: Bruno Brochet
Author: Ulrich Pfeiffer
Author: Patricia J. Bauer
Author: Vicki Anderson
Author: Jean-Claude Dreher