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This book documents the proceedings of the Fourth International Conference on Cognitive Modeling (ICCM), which brought together researchers from diverse backgrounds to compare cognitive models; evaluate models using human data; and further the development, accumulation, and integration of cognitive theory. ICCM provides a worldwide forum for cognitive scientists who build computational cognitive models and test them against empirical cognitive data. New features of the conference included the Newell Award for best student paper, the Siegel-Wolf Award for best applied research paper, and a Doctoral Consortium which provided an opportunity for students to meet their peers and mentors and to explore their dissertation work in an intense but friendly, multi-approach environment. These new features, as well as a comprehensive view of the posters presented at the conference are offered in this volume.
The International Conference on Cognitive Modeling brings together researchers who develop computational models to explain and predict cognitive data. The core theme of the 2004 conference was "Integrating Computational Models," encompassing an integration of diverse data through models of coherent phenomena; integration across modeling approaches; and integration of teaching and modeling. This text presents the proceedings of that conference. The International Conference on Cognitive Modeling 2004 sought to grow the discipline of computational cognitive modeling by providing a sophisticated modeling audience for cutting-edge researchers, in addition to offering a forum for integrating insights across alternative modeling approaches in both basic research and applied settings, and a venue for planning the future growth of the discipline. The meeting included a careful peer-review process of 6-page paper submissions; poster-abstracts to include late-breaking work in the area; prizes for best papers; a doctoral consortium; and competitive modeling symposia that compare and contrast different approaches to the same phenomena.
The International Conference on Cognitive Modeling brings together researchers who develop computational models that explain and predict cognitive data. The 2004 conference encompassed an integration of diverse data through models of coherent phenomena;
This volume features the complete text of the material presented at the Twenty-Fourth Annual Conference of the Cognitive Science Society. As in previous years, the symposium included an interesting mixture of papers on many topics from researchers with diverse backgrounds and different goals, presenting a multifaceted view of cognitive science. The volume includes all papers, posters, and summaries of symposia presented at this leading conference that brings cognitive scientists together. The 2002 meeting dealt with issues of representing and modeling cognitive processes as they appeal to scholars in all subdisciplines that comprise cognitive science: psychology, computer science, neuroscience, linguistics, and philosophy.
Incremental Conceptualization for Language Production discusses the simultaneous actions involved in thinking and speaking, as well as the piecemeal way in which individuals construct an internal representation of the external world and use this internal representation for speaking. Author Markus Guhe presents the first computational model that captures these observations in a cognitively adequate fashion. The volume is an innovative look at the mind’s process of producing semantic representations that can be transformed into language. The first section of the book illustrates four stages of conceptualization: construction of a conceptual representation; selection of content to be verbalized; linearization of the selected content; and generation of preverbal messages. Guhe then analyzes incremental processing — processing that takes place in a piecemeal fashion — and offers a blueprint of incremental models while discussing the dimensions along which the processing principles and the blueprint varies. Finally, incremental processing and conceptualization merge to form the incremental conceptualiser model (inC). The effective use of inC is demonstrated through simulations carried out with the implementation of the model. Intended for researchers in cognitive science, particularly cognitive modeling of language, this volume will also interest researchers in artificial intelligence, computational linguistics, psycholinguistics, and linguistics and psychology.
The aim of the European Cognitive Science Conference is the presentation of empirical, theoretical, and analytic work from all areas of interest in cognitive science, such as artificial intelligence, education, linguistics, neuroscience, philosophy, psychology, and anthropology. The focus is on interdisciplinary work that is either of interest for more than one of the research areas mentioned or integrates research methods from different fields. With contributions by cognitive scientists from 20 different countries, the papers in this volume reflect the origins of this conference, as well as its international scope.
Over the last decade, the topic of prospective memory the encoding, storage and delayed retrieval of intended actions has attracted much interest, and this is reflected in a rapidly growing body of literature: 350 scientific articles have been published on this topic since the appearance of the first edited book in 1996. In addition to the quan
Visualizations are visual representations of non-visual data. They are produced for people to interact with and to make sense of the underlying data. Rapid advances in display technology and computer power have enabled researchers to produce visually appealing pictures. However, the effectiveness of those pictures in conveying the embedded information to end users has not been fully explored. Handbook of Human Centric Visualization addresses issues related to design, evaluation and application of visualizations. Topics include visualization theories, design principles, evaluation methods and metrics, human factors, interaction methods and case studies. This cutting-edge book includes contributions from well-established researchers worldwide, from diverse disciplines including psychology, visualization and human-computer interaction. This handbook is designed for a professional audience composed of practitioners, lecturers and researchers working in the field of computer graphics, visualization, human-computer interaction and psychology. Undergraduate and postgraduate students in science and engineering focused on this topic will also find this book useful as a comprehensive textbook or reference.
Order affects the results you get: Different orders of presenting material can lead to qualitatively and quantitatively different learning outcomes. These differences occur in both natural and artificial learning systems. In Order to Learn shows how order effects are crucial in human learning, instructional design, machine learning, and both symbolic and connectionist cognitive models. Each chapter explains a different aspect of how the order in which material is presented can strongly influence what is learned by humans and theoretical models of learning in a variety of domains. In addition to data, models are provided that predict and describe order effects and analyze how and when they will occur. The introductory and concluding chapters compile suggestions for improving learning through better sequences of learning materials, including how to take advantage of order effects that encourage learning and how to avoid order effects that discourage learning. Each chapter also highlights questions that may inspire further research. Taken together, these chapters show how order effects in different areas can and do inform each other. In Order to Learn will be of interest to researchers and students in cognitive science, education, machine learning.
"This book describes computational models of reading, or models that simulate and explain the mental processes that support the reading of text. The book provides introductory chapters on both reading research and computer models. The central chapters of the book then review what has been learned about reading from empirical research on four core reading processes: word identification, sentence processing, discourse representation, and how these three processes are coordinated with visual processing, attention, and eye-movement control. These central chapters also review an influential sample of computer models that have been developed to explain these key empirical findings, as well as comparative analyses of those models. The final chapter attempts to integrate this empirical and theoretical work be both describing a new comprehensive model of reading, Über-Reader, and reporting several simulations to illustrate how the model accounts for many of the basic phenomena related to reading"--