Axiomatic Concensus Theory in Group Choice and Biomathematics (Frontiers in Applied Mathematics, Series Number 29)

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.

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.