This comprehensive work covers both statistical and symbolic approaches to language processing; it shows how they can be applied to important tasks such as speech recognition, spelling and grammar correction, information extraction, search engines, machine translation, and the creation of spoken-language dialog agents. The following distinguishing features make the text both an introduction to the field and an advanced reference guide.- UNIFIED AND COMPREHENSIVE COVERAGE OF THE FIELDCovers the fundamental algorithms of each field, whether proposed for spoken or written language, whether logical or statistical in origin.- EMPHASIS ON WEB AND OTHER PRACTICAL APPLICATIONSGives readers an understanding of how language-related algorithms can be applied to important real-world problems.- EMPHASIS ON SCIENTIFIC EVALUATIONOffers a description of how systems are evaluated with each problem domain.- EMPERICIST/STATISTICAL/MACHINE LEARNING APPROACHES TO LANGUAGE PROCESSINGCovers all the new statistical approaches, while still completely covering the earlier more structured and rule-based methods.

    In many industries, changes in products and technologies have brought with them new kinds of firms and forms of organization. We are discovering news ways of structuring work, of bringing buyers and sellers together, and of creating and using market information. Although our fast-moving economy often seems to be outside of our influence or control, human beings create the things that create the market forces. Devices, software programs, production processes, contracts, firms, and markets are all the fruit of purposeful action: they are designed. Using the computer industry as an example, Carliss Y. Baldwin and Kim B. Clark develop a powerful theory of design and industrial evolution. They argue that the industry has experienced previously unimaginable levels of innovation and growth because it embraced the concept of modularity, building complex products from smaller subsystems that can be designed independently yet function together as a whole. Modularity freed designers to experiment with different approaches, as long as they obeyed the established design rules. Drawing upon the literatures of industrial organization, real options, and computer architecture, the authors provide insight into the forces of change that drive today's economy.

    Inspired by the Darwinian principle of selective reproduction of the fittest, it views robots as autonomous artificial organisms that develop their own skills in close interaction with the environment and without human intervention. Drawing heavily on biology and ethology, it uses the tools of neural networks, genetic algorithms, dynamic systems, and biomorphic engineering. The resulting robots share with simple biological systems the characteristics of robustness, simplicity, small size, flexibility, and modularity.In evolutionary robotics, an initial population of artificial chromosomes, each encoding the control system of a robot, is randomly created and put into the environment. Each robot is then free to act (move, look around, manipulate) according to its genetically specified controller while its performance on various tasks is automatically evaluated. The fittest robots then reproduce by swapping parts of their genetic material with small random mutations. The process is repeated until the birth of a robot that satisfies the performance criteria.This book describes the basic concepts and methodologies of evolutionary robotics and the results achieved so far. An important feature is the clear presentation of a set of empirical experiments of increasing complexity. Software with a graphic interface, freely available on a Web page, will allow the reader to replicate and vary (in simulation and on real robots) most of the experiments.