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This is the first comprehensive treatment of subjective logic and all its operations. The author developed the approach, and in this book he first explains subjective opinions, opinion representation, and decision-making under vagueness and uncertainty, and he then offers a full definition of subjective logic, harmonising the key notations and formalisms, concluding with chapters on trust networks and subjective Bayesian networks, which when combined form general subjective networks. The author shows how real-world situations can be realistically modelled with regard to how situations are perceived, with conclusions that more correctly reflect the ignorance and uncertainties that result from partially uncertain input arguments. The book will help researchers and practitioners to advance, improve and apply subjective logic to build powerful artificial reasoning models and tools for solving real-world problems. A good grounding in discrete mathematics is a prerequisite.
This book constitutes the refereed proceedings of the 9th International Conference on Ad Hoc Networks, AdHocNets 2017, held in Niagara Falls, Ontario, USA, in September 2017. The 19 full papers were selected from 30 submissions and cover a variety of network paradigms including mobile ad hoc networks (MANETs), sensor networks, vehicular networks, underwater networks, airborne networks, underground networks, personal area networks, device-to-device (D2D) communications in 5G cellular networks, and home networks. The papers present a wide range of applications in civilian, commercial, and military areas.
Over the past several years, cooperative control and optimization have increasingly played a larger and more important role in many aspects of military sciences, biology, communications, robotics, and decision making. At the same time, cooperative systems are notoriously difficult to model, analyze, and solve — while intuitively understood, they are not axiomatically defined in any commonly accepted manner. The works in this volume provide outstanding insights into this very complex area of research. They are the result of invited papers and selected presentations at the Fourth Annual Conference on Cooperative Control and Optimization held in Destin, Florida, November 2003. This book has been selected for coverage in: • Index to Scientific & Technical Proceedings® (ISTP® / ISI Proceedings) • Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings) • CC Proceedings — Engineering & Physical Sciences Contents:Mesh Stability in Formation of Distributed Systems (C Ashokkumar et al.)On the Performance of Heuristics for Broadcast Scheduling (C Commander et al.)Coupled Detection Rates: An Introduction (D Jeffcoat)Decentralized Receding Horizon Control for Multiple UAVs (Y Kuwata & J How)Multitarget Sensor Management of Dispersed Mobile Sensors (R Mahler)K-Means Clustering Using Entropy Minimization (A Okafor & P Pardalos)Possibility Reasoning and the Cooperative Prisoner's Dilemma (H Pfister & J Walls)Coordinating Very Large Groups of Wide Area Search Munitions (P Scerri et al.)A Vehicle Following Methodology for UAV Formations (S Spry et al.)Decentralized Optimization via Nash Bargaining (S Waslander et al.)and other papers Readership: Graduate students and researchers in optimization and control, computer science and engineering. Keywords:Cooperative Systems, Cooperative Control;Optimization;Cooperative NetworksKey Features:25 chapters of creative approaches to modeling, analysis, and synthesis of cooperative systemsResearch results from top researchers in the field of cooperative systemsExciting insights to cooperative systems which have increasingly played a larger and more important role in many aspects of military sciences, biology, communications, robotics, and decision making
Neuronale Netze sind ein Berechenbarkeitsparadigma, das in der Informatik zunehmende Beachtung findet. In diesem Buch werden theoretische Ansätze und Modelle, die in der Literatur verstreut sind, zu einer modellübergreifenden Theorie der künstlichen neuronalen Netze zusammengefügt. Mit ständigem Blick auf die Biologie wird - ausgehend von einfachsten Netzen - gezeigt, wie sich die Eigenschaften der Modelle verändern, wenn allgemeinere Berechnungselemente und Netztopologien eingeführt werden. Jedes Kapitel enthält Beispiele und ist ausführlich illustriert und durch bibliographische Anmerkungen abgerundet. Das Buch richtet sich an Leser, die sich einen Überblick verschaffen oder vorhandene Kenntnisse vertiefen wollen. Es ist als Grundlage für Neuroinformatikvorlesungen an deutschsprachigen Universitäten geeignet.
Prolog, die wohl bedeutendste Programmiersprache der Künstlichen Intelligenz, hat eine einzigartige Verbreitung und Beliebtheit erreicht und gilt als Basis für eine ganze neue Generation von Programmiersprachen und -systemen. Der vorliegenden deutschen Übersetzung des Standardwerks Programming in Prolog liegt die dritte Auflage der englischen Fassung zugrunde. Das Buch ist sowohl Lehrbuch als auch Nachschlagewerk und für alle geeignet, die Prolog als Programmiersprache für die Praxis erlernen und benutzen wollen. Zahlreiche Beispiele zeigen, wie nützliche Programme mit heutigen Prolog-Systemen geschrieben werden können. Die Autoren konzentrieren sich auf den "Kern" von Prolog; alle Beispiele entsprechen diesem Standard und laufen auf den verbreitetsten Prolog-Implementierungen. Zu einigen Implementierungen sind im Anhang Hinweise auf Besonderheiten enthalten.

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