This volume is the third volume of papers originating from the European Mathematical Psychology Group. Earlier volumes were: E. Degreef & J. van Buggenhaut (Eds.), Trends In Mathematical Psychology, Amsterdam, North-Holland Publ. Cy., 1984, and E.E. Roskam & R. Suck (Eds.), Progress in Mathematical Psychology, Amsterdam: Elsevier Science Publ. As the title indicates, this volume presents work in progress, which was reported in one of the recent annual meetings of the European Mathematical Psychology Group. The Group finds it worthwhile to disseminate this work, using a review process which is somewhat less strict, and a publication lag which is shorter, than would be the case for standard international journals. The editor is happy that the meetings of the European Mathematical Psychology Group are regularly attended by colleagues from overseas. Their contributions also appear in this volume, as was the case in earlier volumes. Despite apparent heterogeneity, the reader will observe that European mathemati cal psychologists have a keen interest in basic issues of mathematical modeling and measurement theory, and that also substantive topics, such as decision making, per ception, and performance are studied in the context of formal modeling. Also, and per haps of more than casual importance for future developments, is the fact that theory, experiment, and data analysis go closely together. It should therefore not surprise that psychometric topics, and topics in scaling are represented in this volume, alongside with topics of a more 'purely' mathematical nature.

Contributions to Mathematical Psychology, Psycho§ metrics and Methodology presents the most esteemed research findings of the 22nd European Mathematical Psychology Group meeting in Vienna, Austria, September 1991. The selection of work appearing in this volume contains not only contributions to mathematical psychology in the narrow sense, but also work in psychometrics and methodology, with the common element of all contributions being their attempt to deal with scientific problems in psychology with rigorous mathematics reasoning. The book contains 28 chapters divided into five parts: Perception, Learning, and Cognition; Choice and Reaction Time; Social Systems; Measurement and Psychometrics; and Methodology. It is of interest to all mathematical psychologists, educational psychologists, and graduate students in these areas.

Mathematical psychology is an interdisciplinary area of research in which methods of mathematics, operations research, and computer science in psychology are used. Now more than thirty years old, the field has continued to grow rapidly and has taken on a life of its own. This volume summarizes recent progress in mathematical psychology as seen by some of the leading figures in the field as well as some of its leading young researchers. The papers presented in this volume reflect the most important current directions of research in mathematical psychology. They cover topics in measurement, decision and choice, psychophysics and psychometrics, knowledge representation, neural nets and learning models, and cognitive modeling. Some of the major ideas included are new applications of concepts of measurement theory to social phenomena, new directions in the theory of probabilistic choice, surprising results in nonlinear utility theory, applications of boolean methods in the theory of knowledge spaces, applications of neural net ideas to concept learning, developments in the theory of parallel processing models of response time, new results in inhibition theory, and new concepts about paired associate learning.

This classic text presents problems of learning and teaching mathematics from both a psychological and mathematical perspective. The Psychology of Learning Mathematics, already translated into six languages (including Chinese and Japanese), has been revised for this American Edition to include the author's most recent findings on the formation of mathematical concepts, different kinds of imagery, interpersonal and emotional factors, and a new model of intelligence. The author contends that progress in the areas of learning and teaching mathematics can only be made when such factors as the abstract and hierarchical nature of mathematics, the relation to mathematical symbolism and the distinction between intelligent learning and rote memorization are taken into account and instituted in the classroom.

The art or skill of problem solving in mathematics is mostly relegated to the strategies one can use to solve problems in the field. Although this book addresses that issue, it delves deeply into the psychological aspects that affect successful problem-solving. Such topics as decision-making, judgment, and reasoning as well as using memory effectively and a discussion of the thought processes that could help address certain problem-solving situations.Most books that address problem-solving and mathematics focus on the various skills. This book goes beyond that and investigates the psychological aspects to solving problems in mathematics.

Sometime in the late sixties, one of the editors of this volume realized that the mathematica psychologists in Europe-an odd lot mostly concentrated in Germany, the Netherlands, France, England and Belgium-were suffering from an acute sense of isolation. The papers that they presented at meetings of their national or regional societies had to be 'sanitized' to the point of misrepresentation. They were misunderstood. The mood was grim, depression was lurking. He decided that urgent action was required: a European gathering of mathematical psychologists was called in April 1971. Not being foolhardy, however, he took the precaution of choosing Paris as the meeting place. Around thirty mathematical psychologists received an invitation. They all came, justifying at least Paris's reputation. The meeting took place at the 'Maison des Belges' of the Cite Universitaire, Boulevard Jourdan, in front of the Parc Montsouris. As far as everyone remembers, the meeting was a full success. A happy birth had taken place. This editor then irresponsibly accepted a position in a university in the US, leaving an infant to the whims of the passers-by. Fortunately, a godfather came along. The next meeting took place in Nijmegen, in November 1971, under the loving care of Eddy Roskam. A tradition was established. The third meeting was in Oxford (1972); then in Marseilles (1973), Regensburg (1974), Stirling (1975), Stockholm (1976) . . . The infant became a toddler, then a vigorous child. This annual meeting is now an important event in the field.

Mathematical Psychology and Psychophysiology promotes an understanding of the mind and its neural substrates by applying interdisciplinary approaches to issues concerning behavior and the brain. The contributions present model from many disciplines that share common, conceptual, functional, or mechanistic substrates and summarize recent models and data from neural networks, mathematical genetics, psychoacoustics, olfactory coding, visual perception, measurement, psychophysics, cognitive development, and other areas. The contributors to Mathematical Psychology and Psychophysiology show the conceptual and mathematical interconnectedness of several approaches to the fundamental scientific problem of understanding mind and brain. The book's interdisciplinary approach permits a deeper understanding of theoretical advances as it formally structures a broad overview of the data.

First multi-year cumulation covers six years: 1965-70.

Cutting edge research from a diverse range of viewpoints Central section dedicated to the arithmetical development of memory.

This Oxford Handbook offers a comprehensive and authoritative review of important developments in computational and mathematical psychology. With chapters written by leading scientists across a variety of subdisciplines, it examines the field's influence on related research areas such as cognitive psychology, developmental psychology, clinical psychology, and neuroscience. The Handbook emphasizes examples and applications of the latest research, and will appeal to readers possessing various levels of modeling experience. The Oxford Handbook of Computational and mathematical Psychology covers the key developments in elementary cognitive mechanisms (signal detection, information processing, reinforcement learning), basic cognitive skills (perceptual judgment, categorization, episodic memory), higher-level cognition (Bayesian cognition, decision making, semantic memory, shape perception), modeling tools (Bayesian estimation and other new model comparison methods), and emerging new directions in computation and mathematical psychology (neurocognitive modeling, applications to clinical psychology, quantum cognition). The Handbook would make an ideal graduate-level textbook for courses in computational and mathematical psychology. Readers ranging from advanced undergraduates to experienced faculty members and researchers in virtually any area of psychology--including cognitive science and related social and behavioral sciences such as consumer behavior and communication--will find the text useful.