AnnotationOCLC-licensed vendor bibliographic record.
Translated from the German."This classic 1936 work in vision science, written by a leading figure in Germany's Gestalt movement in psychology and appearing in English for the first time, addresses topics that remain of major interest to vision researchers today. Wolfgang Metzger's main argument, drawn from Gestalt theory, is that the objects we perceive in visual experience are not the objects …
Looking at ways to encode prior knowledge and to extract, refine, and revise knowledge within a neurocomputing system.Neurocomputing methods are loosely based on a model of the brain as a network of simple interconnected processing elements corresponding to neurons. These methods derive their power from the collective processing of artificial neurons, the chief advantage being that such systems…
Modeling and implementing dynamical systems is a central problem in artificial intelligence, robotics, software agents, simulation, decision and control theory, and many other disciplines. In recent years, a new approach to representing such systems, grounded in mathematical logic, has been developed within the AI knowledge-representation community. This book presents a comprehensive treatment …
A reassessment of the Jesuit contributions to the emergence of the scientific worldview.Founded in 1540, the Society of Jesus was viewed for centuries as an impediment to the development of modern science. The Jesuit educational system was deemed conservative and antithetical to creative thought, while the Order and its members were blamed by Galileo, Descartes, and their disciples for virtuall…
This book looks at multiagent systems that consist of teams of autonomous agents acting in real-time, noisy, collaborative, and adversarial environments. The book makes four main contributions to the fields of machine learning and multiagent systems. First, it describes an architecture within which a flexible team structure allows member agents to decompose a task into flexible roles and to swi…
In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by…
Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifier--a limited, but well-established and comprehensively studied model--and extends its applicability to a wide range of nonlinear pattern-recognition tasks such as natural language processing, machine vision, and biological sequence analysis. This…
"MIT Press."An exploration of the techniques for analyzing the behavior of one- and two-dimensional iterative networks formed of discrete, or logical elements, showing that most questions about the behavior of iterative systems are recursively undecidable.Title from vendor webpage (IEEE Xplore; viewed on Feb. 14, 2013).An exploration of the techniques for analyzing the behavior of one- and two-…
Papers from a conference held in spring 2001 at the University of Scranton.As our scientific and technical abilities expand at breathtaking speeds, concern that modern genetics and bioengineering are leading us to a posthuman future is growing. Is Human Nature Obsolete? poses the overarching question of what it is to be human against the background of these current advances in biotechnology. It…