Hiroaki Kitano

Hiroaki Kitano is Director of the ERATO Kitano Symbiotic Systems Project of the Japan Science and Technology Corporation and a Senior Researcher at Sony Computer Science Laboratories, Inc.

  • Foundations of Systems Biology

    Foundations of Systems Biology

    Hiroaki Kitano

    An overview of the methodologies and techniques of the emerging field of systems biology.

    The emerging field of systems biology involves the application of experimental, theoretical, and modeling techniques to the study of biological organisms at all levels, from the molecular, through the cellular, to the behavioral. Its aim is to understand biological processes as whole systems instead of as isolated parts. Developments in the field have been made possible by advances in molecular biology—in particular, new technologies for determining DNA sequence, gene expression profiles, protein-protein interactions, and so on. Foundations of Systems Biology provides an overview of the state of the art of the field. The book covers the central topics of systems biology: comprehensive and automated measurements, reverse engineering of genes and metabolic networks from experimental data, software issues, modeling and simulation, and system-level analysis.

    • Hardcover $12.75
  • Massively Parallel Artificial Intelligence

    Massively Parallel Artificial Intelligence

    Hiroaki Kitano and James A. Hendler

    The increased sophistication and availability of massively parallel supercomputers has had two major impacts on research in artificial intelligence, both of which are addressed in this collection of exciting new AI theories and experiments. Massively parallel computers have been used to push forward research in traditional AI topics such as vision, search, and speech. More important, these machines allow AI to expand in exciting new ways by taking advantage of research in neuroscience and developing new models and paradigms, among them associate memory, neural networks, genetic algorithms, artificial life, society-of-mind models, and subsumption architectures. A number of chapters show that massively parallel computing enables AI researchers to handle significantly larger amounts of data in real time, which changes the way that AI systems can be built, which in turn makes memory-based reasoning and neural-network-based vision systems become practical. Other chapters present the contrasting view that massively parallel computing provides a platform to model and build intelligent systems by simulating the (massively parallel) processes that occur in nature.

    • Paperback $11.75