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Engineering of Intelligent Systems
This book constitutes the refereed proceedings of the 14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Export Systems, IEA/AIE 2001, held in Budapest, Hungary in June 2001. The 104 papers presented were carefully reviewed and selected from a total of 140 submissions. The proceedings offer topical sections on searching, knowledge representation, model-based reasoning, machine learning, data mining, soft computing, evolutionary algorithms, distributed problem solving, export systems, pattern and speech recognition, vision language processing, planning and scheduling, robotics, autonomous agents, design, control, manufacturing systems, finance and business, software engineering, and intelligent tutoring.
Neural Networks and Soft Computing
This volume presents new trends and developments in soft computing techniques. Topics include: neural networks, fuzzy systems, evolutionary computation, knowledge discovery, rough sets, and hybrid methods. It also covers various applications of soft computing techniques in economics, mechanics, medicine, automatics and image processing. The book contains contributions from internationally recognized scientists, such as Zadeh, Bubnicki, Pawlak, Amari, Batyrshin, Hirota, Koczy, Kosinski, Novák, S.-Y. Lee, Pedrycz, Raudys, Setiono, Sincak, Strumillo, Takagi, Usui, Wilamowski and Zurada. An excellent overview of soft computing methods and their applications.
Towards a Unified Modeling and Knowledge-Representation based on Lattice Theory
This research monograph proposes a unified, cross-fertilizing approach for knowledge-representation and modeling based on lattice theory. The emphasis is on clustering, classification, and regression applications. It presents novel tools and useful perspectives for effective pattern classification. The material is multi-disciplinary based on on-going research published in major scientific journals and conferences.
Liability for Crimes Involving Artificial Intelligence Systems
The book develops a general legal theory concerning the liability for offenses involving artificial intelligence systems. The involvement of the artificial intelligence systems in these offenses may be as perpetrators, accomplices or mere instruments. The general legal theory proposed in this book is based on the current criminal law in most modern legal systems. In most modern countries, unmanned vehicles, sophisticated surgical systems, industrial computing systems, trading algorithms and other artificial intelligence systems are commonly used for both industrial and personal purposes. The question of legal liability arises when something goes wrong, e.g. the unmanned vehicle is involved i...
Scalable Optimization via Probabilistic Modeling
I’m not usually a fan of edited volumes. Too often they are an incoherent hodgepodge of remnants, renegades, or rejects foisted upon an unsuspecting reading public under a misleading or fraudulent title. The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited volumes fail. For example, take the title, Scalable Optimization via Probabilistic M- eling: From Algorithms to Applications. You need not worry that you’re going to pick up this book and ?nd stray articles about anything else. This book focuseslikealaserbeamononeofthehottesttopicsinevolution...
Artificial Intelligence in Medicine
This book constitutes the refereed proceedings of the 11th Conference on Artificial Intelligence in Medicine in Europe, AIME 2007, held in Amsterdam, The Netherlands in July 2007. The 28 revised full papers and 38 revised short papers presented were carefully reviewed and selected from 137 submissions. The papers are organized in topical sections on agent-based systems, temporal data mining, machine learning and knowledge discovery, text mining, natural language processing and generation, ontologies, decision support systems, applications of AI-based image processing techniques, protocols and guidelines, as well as workflow systems.
Nonlinear Control of Dynamic Networks
Significant progress has been made on nonlinear control systems in the past two decades. However, many of the existing nonlinear control methods cannot be readily used to cope with communication and networking issues without nontrivial modifications. For example, small quantization errors may cause the performance of a "well-designed" nonlinear control system to deteriorate. Motivated by the need for new tools to solve complex problems resulting from smart power grids, biological processes, distributed computing networks, transportation networks, robotic systems, and other cutting-edge control applications, Nonlinear Control of Dynamic Networks tackles newly arising theoretical and real-worl...
Fundamentals in Modeling and Control of Mobile Manipulators
Mobile manipulators combine the advantages of mobile platforms and robotic arms, extending their operational range and functionality to large spaces and remote, demanding, and/or dangerous environments. They also bring complexity and difficulty in dynamic modeling and control system design.
Real-Time Rendering
Consumers today expect extremely realistic imagery generated in real time for interactive applications such as computer games, virtual prototyping, and scientific visualisation. However, the increasing demands for fidelity coupled with rapid advances in hardware architecture pose a challenge: how do you find optimal, sustainable solutions to accommodate both speed of rendering and quality? Real-Time Rendering: Computer Graphics with Control Engineering presents a novel framework for solving the perennial challenge of resource allocation and the trade-off between quality and speed in interactive computer graphics rendering. Conventional approaches are mainly based on heuristics and algorithms...
Intelligent Diagnosis and Prognosis of Industrial Networked Systems
In an era of intense competition where plant operating efficiencies must be maximized, downtime due to machinery failure has become more costly. To cut operating costs and increase revenues, industries have an urgent need to predict fault progression and remaining lifespan of industrial machines, processes, and systems. An engineer who mounts an acoustic sensor onto a spindle motor wants to know when the ball bearings will wear out without having to halt the ongoing milling processes. A scientist working on sensor networks wants to know which sensors are redundant and can be pruned off to save operational and computational overheads. These scenarios illustrate a need for new and unified pers...
