Expert Systems
Expert Systems

Author: Cornelius T. Leondes

Publisher: Elsevier

Published: 2001-09-26

Total Pages: 2125

ISBN-13: 0080531458

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This six-volume set presents cutting-edge advances and applications of expert systems. Because expert systems combine the expertise of engineers, computer scientists, and computer programmers, each group will benefit from buying this important reference work. An "expert system" is a knowledge-based computer system that emulates the decision-making ability of a human expert. The primary role of the expert system is to perform appropriate functions under the close supervision of the human, whose work is supported by that expert system. In the reverse, this same expert system can monitor and double check the human in the performance of a task. Human-computer interaction in our highly complex world requires the development of a wide array of expert systems. Expert systems techniques and applications are presented for a diverse array of topics including Experimental design and decision support The integration of machine learning with knowledge acquisition for the design of expert systems Process planning in design and manufacturing systems and process control applications Knowledge discovery in large-scale knowledge bases Robotic systems Geograhphic information systems Image analysis, recognition and interpretation Cellular automata methods for pattern recognition Real-time fault tolerant control systems CAD-based vision systems in pattern matching processes Financial systems Agricultural applications Medical diagnosis

Recent Research in Control Engineering and Decision Making
Recent Research in Control Engineering and Decision Making

Author: Olga Dolinina

Publisher: Springer

Published: 2019-01-28

Total Pages: 792

ISBN-13: 3030120724

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This book constitutes the full papers and short monographs developed on the base of the refereed proceedings of the International Conference on Information Technologies: Information and Communication Technologies for Research and Industry (ICIT-2019), held in Saratov, Russia in February 2019. The book brings accepted papers which present new approaches and methods of solving problems in the sphere of control engineering and decision making for the various fields of studies: industry and research, ontology-based data simulation, smart city technologies, theory and use of digital signal processing, cognitive systems, robotics, cybernetics, automation control theory, image recognition technologies, and computer vision. Particular emphasis is laid on modern trends, new approaches, algorithms and methods in selected fields of interest. The presented papers were accepted after careful reviews made by at least three independent reviewers in a double-blind way. The acceptance level was about 60%. The chapters are organized thematically in several areas within the following tracks: • Models, Methods & Approaches in Decision Making Systems • Mathematical Modelling for Industry & Research • Smart City Technologies The conference is focused on development and globalization of information and communication technologies (ICT), methods of control engineering and decision making along with innovations and networking, ICT for sustainable development and technological change, and global challenges. Moreover, the ICIT-2019 served as a discussion area for the actual above-mentioned topics. The editors believe that the readers will find the proceedings interesting and useful for their own research work.

Real-Time Expert Systems Computer Architecture
Real-Time Expert Systems Computer Architecture

Author: R.F. Hodson

Publisher: CRC Press

Published: 2018-01-17

Total Pages: 213

ISBN-13: 135109310X

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Expert systems and real-time systems technology have been developed independently. Expert systems have been successfully implemented in many complex applications traditionally performed by human experts. Real-time systems have been successfully applied in areas requiring interaction with dynamic environments, control and monitoring applications for example. Merging these two technologies will yield intelligent systems capable of interacting with complex dynamic environments, an area in which human operators exhibit poor productivity, due to cognitive overload.

Empirical Foundations of Information and Software Science V
Empirical Foundations of Information and Software Science V

Author: Pranas Zunde

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 455

ISBN-13: 1468458620

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This is the proceedings of the Sixth Symposium on Empirical Foundations of Information and Software Sciences (EFISS), which was held in Atlanta, Georgia, on October 19-21, 1988. The purpose of the symposia is to explore subjects and methods of scientific inquiry which are of common interest to information and software sciences, and to identify directions of research that would benefit from the mutual interaction of these two disciplines. The main theme of the sixth symposium was modeling in information and software engineering, with emphasis on methods and tools of modeling. The symposium covered topics such as models of individual and organizational users of information systems, methods of selecting appropriate types of models for a given type of users and a given type of tasks, deriving models from records of system usage, modeling system evolution, constructing user and task models for adaptive systems, and models of system architectures. This symposium was sponsored by the School of Information and Computer Science of the Georgia Institute of Technology and by the U.S. Army Institute for Research in Management Information, Communications, and Computer Sciences (AIRMICS). 17le Editors vii CONTENTS 1 I. KEYNOTE ADDRESS ............................................. .

Decision Making Under Uncertainty
Decision Making Under Uncertainty

Author: Mykel J. Kochenderfer

Publisher: MIT Press

Published: 2015-07-24

Total Pages: 350

ISBN-13: 0262331713

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An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.