This book is out of a workshop organized to address questions like these. The meeting was sponsored by the Santa Fe Institute and held at Sol y Sam- bra in Santa Fe, New Mexico, during July, 1993. It brought together a group of about 20 scientists from the disciplines of biology, psychology, and computer science, all studying interactions between the evolution of populations and individuals' adaptations in those populations, and all of whom make some use of computational tools in their work.

The theory of evolution has been most successful explaining the emergence of new species in terms of their morphological traits. Ethologists teach that behaviors, too, qualify as first-class phenotypic features, but evolutionary accounts of behaviors have been much less satisfactory. In part this is because maturational "programs" transforming genotype to phenotype are "open" to environmental influences affected by behaviors. Further, many organisms are able to continue to modify their behavior, i.e., learn, even after fully mature. This creates an even more complex relationship between the genotypic features underlying the mechanisms of maturation and learning and the adapted behaviors ultimately selected.A meeting held at the Santa Fe Institute during the summer of 1993 brought together a small group of biologists, psychologists, and computer scientists with shared interests in questions such as these. This volume consists of papers that explore interacting adaptive systems from a range of interdisciplinary perspectives. About half of the articles are classic, seminal references on the subject, ranging from biologists like Lamarck and Waddington to psychologists like Piaget and Skinner. The other half represent new work by the workshop participants. The role played by mathematical and computational tools, both as models of natural phenomena and as algorithms useful in their own right, is particularly emphasized in these new papers. In all cases, the prefaces help to put the older papers in a modern context. For the new papers, the prefaces have been written by colleagues from a discipline other than the paper's authors, and highlight, for example, what a computer scientist can learn from a biologist's model, or vice versa. Through these cross-disciplinary "dialogues" and a glossary collecting multidisciplinary connotations of pivotal terms, the process of interdisciplinary investigation itself becomes a central theme.

The World Wide Web is rapidly filling with more text than anyone could have imagined a short time ago. However, the task of determining which data is relevant has become appreciably harder. In this original new work Richard Belew brings a cognitive science perspective to the study of information as a computer science discipline. He introduces the idea of Finding Out About (FOA), the process of actively seeking out information relevant to a topic of interest. Belew describes all facets of FOA, ranging from creating a good characterization of what the user seeks to evaluating the successful performance of search engines. His volume clearly shows how to build many of the tools that are useful for searching collections of text and other media. While computer scientists make up the book's primary audience, Belew skillfully presents technical details in a manner that makes important themes accessible to readers more comfortable with words than equations. Resources are available from the book's web site