The chapters collected in this volume represent the "state-of-the-art" of research on the development of intentional action and intentional understanding--topics that are at the intersection of current research on imitation, early understanding of mental states, goal-directed behavior in nonhuman animals, executive function, language acquisition, and narrative understanding, to name just a few of the relevant foci. Collectively, the contributors demonstrate that intentionality is a key issue in the cognitive and social sciences. Moreover, in a way that was anticipated more than a century ago by the seminal work of J. Mark Baldwin, they are beginning to reveal how the control of action is related in development to children's emerging self-conscious and their increasingly sophisticated appreciation of other people's perspectives. This volume brings together the world's leading researchers on early social and cognitive development in an in-depth exploration of children's understanding of themselves and others.

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.

Focuses on the topic of leadership in the library and information professions, providing an overview of institutes, programs and activities occurring around the world. This title provides insights to those interested in workforce planning strategies aimed at addressing shortages of library leaders.

This definitive volume is the result of collaboration by top scholars in the field of children's cognition. New edition offers an up-to-date overview of all the major areas of importance in the field, and includes new data from cognitive neuroscience and new chapters on social cognitive development and language Provides state-of-the-art summaries of current research by international specialists in different areas of cognitive development Spans aspects of cognitive development from infancy to the onset of adolescence Includes chapters on symbolic reasoning, pretend play, spatial development, abnormal cognitive development and current theoretical perspectives

Psychology Library Editions: Child Development (20 Volume set) brings together a diverse number of titles across many areas of developmental psychology, from children’s play to language development. The series of previously out-of-print titles, originally published between 1930 and 1993, with the majority from the 70s and 80s, includes contributions from many respected authors in the field and charts the progression of the field over this time.

Highlights the roles of intention and intentionality in social cognition.

Children are already learning at birth, and they develop and learn at a rapid pace in their early years. This provides a critical foundation for lifelong progress, and the adults who provide for the care and the education of young children bear a great responsibility for their health, development, and learning. Despite the fact that they share the same objective - to nurture young children and secure their future success - the various practitioners who contribute to the care and the education of children from birth through age 8 are not acknowledged as a workforce unified by the common knowledge and competencies needed to do their jobs well. Transforming the Workforce for Children Birth Through Age 8 explores the science of child development, particularly looking at implications for the professionals who work with children. This report examines the current capacities and practices of the workforce, the settings in which they work, the policies and infrastructure that set qualifications and provide professional learning, and the government agencies and other funders who support and oversee these systems. This book then makes recommendations to improve the quality of professional practice and the practice environment for care and education professionals. These detailed recommendations create a blueprint for action that builds on a unifying foundation of child development and early learning, shared knowledge and competencies for care and education professionals, and principles for effective professional learning. Young children thrive and learn best when they have secure, positive relationships with adults who are knowledgeable about how to support their development and learning and are responsive to their individual progress. Transforming the Workforce for Children Birth Through Age 8 offers guidance on system changes to improve the quality of professional practice, specific actions to improve professional learning systems and workforce development, and research to continue to build the knowledge base in ways that will directly advance and inform future actions. The recommendations of this book provide an opportunity to improve the quality of the care and the education that children receive, and ultimately improve outcomes for children.