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Originally published in 1974, this volume presents empirical and theoretical investigations of the role of meaning in psychological processes. A theory is proposed for the representation of the meaning of texts, employing ordered lists of propositions. The author explores the adequacy of this representation, with respect to the demands made upon such formulations by logicians and linguists. A sufficiently large number of problems are encompassed by the propositional theory to justify its use in psychological research into memory and language comprehension. A number of different experiments are reported on a wide variety of topics, and these test central portions of this theory, and any that purports to deal with how humans represent meaning. Among the topics discussed are the role of lexical decomposition in comprehension and memory, propositions as the units of recall, and the effects of the number of propositions in a text base upon reading rate and recall. New problems are explored, such as inferential processes during reading, differences in levels of memory for text, and retrieval speed for textual information. On the other hand, a study of retrieval from semantic memory focusses on a problem of much current research. The final review chapter relates the present work to other current research in the area at the time.
First published in 1974, Attributes of Memory rejected the prevalent stress on the structure of memory. It suggests that the view of memory as a sequence of stores through which information passes is mistaken. Instead, the author emphasizes the coding process of memory by which the nominal stimulus, the stimulus as presented, is transformed into the functional stimulus, the stimulus as coded. Dr Herriot proposes that there are many different forms of coding, and that efficiency of recall or recognition performance is a function of the nature of coding employed. He suggests that the subject’s linguistic system is the most frequently employed linguistic device; that is, that the underlying attributes and rules of language are used automatically when material is verbal. Since the basic function of language is to communicate meaning, those forms of coding which are meaningful in nature are most effective in memory. The book cites a great deal of experimental evidence, including many studies of the time. As well as stating a point of view, it should be useful to undergraduate and postgraduate students as a review of the early literature, read in its historical context.
The purpose of this handbook, originally published in 1984, was to provide a compreh- sive review of current clinical descriptions, research , and theories of psychopathology. Descriptive psychopathology is a ?eld that forms the foundation of clinical practice and research in clinical psychology, psychiatry, psychiatric social work, psychiatric nursing, and allied professions in mental health. Since the 1st edition, the editors have devised and updated a handbook to cover both general and speci?c topics in psychopathology that would be useful to researchers, practitioners, and graduate or other advanced students in the mental health and behavioral medicine professions. To implement this plan, we have very carefully chosen colleagues whom we respect for their expertise in particular ?elds. These authors include both clinicians and researchers who have outstanding national reputations, as well as more junior behavioral scientists and clinicians who, in our opinion, will achieve similar recognition in the future. The excellent chapters in this book lead us to believe that we have chosen wisely. We would like to express our appreciation to these authors for their outstanding contributions and cooperation.
Embedded in a historical context, this is a novel approach to memory involving goals, cues, information, opportunity to learn, and noise.
First published in 1980. This is a volume of the proceedings of the Eighth International Symposium on Attention and Performance held in Princeton, New Jersey, USA, from August 20th to 25th 1978.
This brief edition contains two major parts. The first is the historical analysis of associationism and its countertraditions, which still provides the framework used to relate current research to an important intellectual tradition. The second part of the book reproduces the major components of the HAM theory. In our view, the major contribution of that theory was the propositional network analyses of memory and the placement of those representational assumptions into an information-processing framework. This book is smaller than the previous book on HAM thanks to a re-evaluation of certain sections which have been deleted--some due to out of date information, some because the analyses presented have been replaced by better ones. This book makes the more important points of the original HAM book available at a more economical price. - from the preface.
Calculus of Thought: Neuromorphic Logistic Regression in Cognitive Machines is a must-read for all scientists about a very simple computation method designed to simulate big-data neural processing. This book is inspired by the Calculus Ratiocinator idea of Gottfried Leibniz, which is that machine computation should be developed to simulate human cognitive processes, thus avoiding problematic subjective bias in analytic solutions to practical and scientific problems. The reduced error logistic regression (RELR) method is proposed as such a "Calculus of Thought." This book reviews how RELR's completely automated processing may parallel important aspects of explicit and implicit learning in neural processes. It emphasizes the fact that RELR is really just a simple adjustment to already widely used logistic regression, along with RELR's new applications that go well beyond standard logistic regression in prediction and explanation. Readers will learn how RELR solves some of the most basic problems in today's big and small data related to high dimensionality, multi-colinearity, and cognitive bias in capricious outcomes commonly involving human behavior. - Provides a high-level introduction and detailed reviews of the neural, statistical and machine learning knowledge base as a foundation for a new era of smarter machines - Argues that smarter machine learning to handle both explanation and prediction without cognitive bias must have a foundation in cognitive neuroscience and must embody similar explicit and implicit learning principles that occur in the brain
First published in 1982. Routledge is an imprint of Taylor & Francis, an informa company.