Axiomatic Consensus Theory in Group Choice and Biomathematics

William F.E. Day, F.R. McMorris

ISBN 10: 0898715512 / ISBN 13: 9780898715514

Published by Society for Industrial and Applied Mathematics,U.S., US, 2003

About this Item

Bioconsensus is a rapidly evolving scientific field in which consensus methods, often developed for use in social choice theory, are adapted for such areas of the biological sciences as taxonomy, systematics, and evolutionary and molecular biology. Typically, after several alternatives are produced using different data sets, methods or algorithms, one needs to find a consensus solution.The axiomatic approach of this book explores the existence or nonexistence of consensus rules that satisfy particular sets of desirable well-defined properties. The axiomatic research reviewed here focuses first on the area of group choice, then in areas of biomathematics where the objects of interest represent partitions of a set, hierarchical structures, phylogenetic trees, or molecular sequences.This book provides a unique comprehensive review of axiomatic consensus theory in biomathematics as it has developed over the past 30 years. Established here are the theory's basic results using standard terminology and notation and with uniform attention to rigor and detail. This book cites both traditional and current literature and poses open problems that remain to be solved. The bibliographic notes in each chapter place the described work within a general context while providing useful pointers to relevant research. The bibliographic references are a valuable resource for both students and experts in the field.

Seller Inventory # LU-9780898715514

Bibliographic Details

• Title: Axiomatic Consensus Theory in Group Choice and Biomathematics
• Publisher: Society for Industrial and Applied Mathematics,U.S., US
• Publication Date: 2003
• Language: English
• ISBN 10: 0898715512
• ISBN 13: 9780898715514
• Binding: Paperback
• Condition: New
• Dimensions: 18.42W x 1.27H x 25.4D centimeters 18.42 centimeters width by 1.27 centimeters height by 25.4 centimeters depth
• Weight: 321 grams

About this title

Synopsis

Bioconsensus is a rapidly evolving scientific field in which consensus methods, often developed for use in social choice theory, are adapted for such areas of the biological sciences as taxonomy, systematics, and evolutionary and molecular biology. Typically, after several alternatives are produced using different data sets, methods or algorithms, one needs to find a consensus solution. The axiomatic approach of this book explores the existence or nonexistence of consensus rules that satisfy particular sets of desirable well-defined properties. The axiomatic research reviewed here focuses first on the area of group choice, then in areas of biomathematics where the objects of interest represent partitions of a set, hierarchical structures, phylogenetic trees, or molecular sequences.

About the Author

William H. E. Day has been Professor of Computer Science at Memorial University of Newfoundland, Associate of the Canadian Institute for Advanced Research, and Gastprofessor at the Institute of Statistics, Rheinisch-Westfaeliche Technische Hochschule, Aachen. He has served as president of the International Federation of Classification Societies as well as the Classification Society of North America. He received the President's Award for Outstanding Research at Memorial University of Newfoundland. His publications apply theoretical computer science or discrete mathematics to problems in the biological or social sciences.

F. R. McMorris is Dean of the College of Science and Letters and Professor of Applied Mathematics at the Illinois Institute of Technology. Before arriving in Illinois, he spent 15 years at the University of Louisville where he was Assistant Vice President for Research, Distinguished University Scholar and Professor of Mathematics. He also has held positions at the Office of Naval Research and Bowling Green State University. His research interests include applied discrete mathematics, mathematical and computational biology, graph theory and combinatorics, classification theory and location theory.