Theoretical And Computational Models Of Word Learning Trends In Psychology And Artificial Intelligence

The process of learning words and languages may seem like an instinctual trait, inherent to nearly all humans from a young age. However, a vast range of complex research and information exists in detailing the complexities of the process of word learning. Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence strives to combine cross-disciplinary research into one comprehensive volume to help readers gain a fuller understanding of the developmental processes and influences that makeup the progression of word learning. Blending together developmental psychology and artificial intelligence, this publication is intended for researchers, practitioners, and educators who are interested in language learning and its development as well as computational models formed from these specific areas of research.

The fields of computer vision and image processing are constantly evolving as new research and applications in these areas emerge. Staying abreast of the most up-to-date developments in this field is necessary in order to promote further research and apply these developments in real-world settings. Computer Vision and Image Processing in Intelligent Systems and Multimedia Technologies features timely and informative research on the design and development of computer vision and image processing applications in intelligent agents as well as in multimedia technologies. Covering a diverse set of research in these areas, this publication is ideally designed for use by academicians, technology professionals, students, and researchers interested in uncovering the latest innovations in the field.

Stigma continues to play an integral role in the multifaceted issues facing mental health. While identifying a clear operational definition of stigma has been a challenge in the field, the issues related to stigma grossly affect not only the mental health population but society as a whole. Deconstructing Stigma in Mental Health provides emerging research on issues related to stigma as a whole including ignorance, prejudice, and discrimination. While highlighting issues such as stigma and its role in mental health and how stigma is perpetuated in society, this publication explores the historical context of stigma, current issues and resolutions through intersectional collaboration, and the deconstruction of mental health stigmas. This book is a valuable resource for mental health administrators and clinicians, researchers, educators, policy makers, and psychology professionals seeking information on current mental health stigma trends.

This volume presents peer-reviewed versions of papers presented at the 14th Neural Computation and Psychology Workshop (NCPW14), which took place in July 2014 at Lancaster University, UK. The workshop draws international attendees from the cutting edge of interdisciplinary research in psychology, computational modeling, artificial intelligence and psychology, and aims to drive forward our understanding of the mechanisms underlying a range of cognitive processes.

Dynamic Thinking: A Primer on Dynamic Field Theory introduces the reader to a new approach to understanding cognitive and neural dynamics using the concepts of Dynamic Field Theory (DFT). Dynamic Neural Fields are formalizations of how neural populations represent the continuous dimensions of perceptual features, movements, and cognitive decisions. The concepts of DFT establish links between brain and behavior, revealing ways in which models of brain function can be tested with both neural and behavioral measures. Thus, DFT bridges the gap between brain and behavior, between neuroscience and the behavioral sciences. The book provides systematic tutorials on the central concepts of DFT and their grounding in both dynamical systems theory and neurophysiology. The concrete mathematical implementation of these concepts is laid out, supported by hands-on exercises that make use of interactive simulators in MATLAB. The book also contains a large set of exemplary case studies in which the concepts and associated models are used to understand how elementary forms of embodied cognition emerge and develop.

In recent years the field has seen an increasing realisation that the full complexity of language acquisition demands theories that (a) explain how children integrate information from multiple sources in the environment, (b) build linguistic representations at a number of different levels, and (c) learn how to combine these representations in order to communicate effectively. These new findings have stimulated new theoretical perspectives that are more centered on explaining learning as a complex dynamic interaction between the child and her environment. This book is the first attempt to bring some of these new perspectives together in one place. It is a collection of essays written by a group of researchers who all take an approach centered on child-environment interaction, and all of whom have been influenced by the work of Elena Lieven, to whom this collection is dedicated.

Looking at and listening to picture and story books is a ubiquitous activity, frequently enjoyed by many young children and their parents. Well before children can read for themselves they are able to learn from books. Looking at and listening to books increases children’s general knowledge, understanding about the world and promotes language acquisition. This collection of papers demonstrates the breadth of information pre-reading children learn from books and increases our understanding of the social and cognitive mechanisms that support this learning. Our hope is that this Research Topic/eBook will be useful for researchers as well as educational practitioners and parents who are interested in optimizing children’s learning.