Classifying Intelligence in Machines: A Taxonomy of Intelligent Control

Classifying Intelligence in Machines: A Taxonomy of Intelligent Control PDF Author: Callum Wilson
Publisher: Infinite Study
ISBN:
Category : Education
Languages : en
Pages : 19

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Book Description
The quest to create machines that can solve problems as humans do leads us to intelligent control. This field encompasses control systems that can adapt to changes and learn to improve their actions—traits typically associated with human intelligence. In this work we seek to determine how intelligent these classes of control systems are by quantifying their level of adaptability and learning. First we describe the stages of development towards intelligent control and present a definition based on literature. Based on the key elements of this definition, we propose a novel taxonomy of intelligent control methods, which assesses the extent to which they handle uncertainties in three areas: the environment, the controller, and the goals. This taxonomy is applicable to a variety of robotic and other autonomous systems, which we demonstrate through several examples of intelligent control methods and their classifications. Looking at the spread of classifications based on this taxonomy can help researchers identify where control systems can be made more intelligent.

Classifying Intelligence in Machines: A Taxonomy of Intelligent Control

Classifying Intelligence in Machines: A Taxonomy of Intelligent Control PDF Author: Callum Wilson
Publisher: Infinite Study
ISBN:
Category : Education
Languages : en
Pages : 19

Get Book Here

Book Description
The quest to create machines that can solve problems as humans do leads us to intelligent control. This field encompasses control systems that can adapt to changes and learn to improve their actions—traits typically associated with human intelligence. In this work we seek to determine how intelligent these classes of control systems are by quantifying their level of adaptability and learning. First we describe the stages of development towards intelligent control and present a definition based on literature. Based on the key elements of this definition, we propose a novel taxonomy of intelligent control methods, which assesses the extent to which they handle uncertainties in three areas: the environment, the controller, and the goals. This taxonomy is applicable to a variety of robotic and other autonomous systems, which we demonstrate through several examples of intelligent control methods and their classifications. Looking at the spread of classifications based on this taxonomy can help researchers identify where control systems can be made more intelligent.

Machine Learning: Concepts, Methodologies, Tools and Applications

Machine Learning: Concepts, Methodologies, Tools and Applications PDF Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1609608194
Category : Computers
Languages : en
Pages : 2174

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Book Description
"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe

Proceedings of International Conference on Communication and Artificial Intelligence

Proceedings of International Conference on Communication and Artificial Intelligence PDF Author: Vishal Goyal
Publisher: Springer Nature
ISBN: 9813365463
Category : Technology & Engineering
Languages : en
Pages : 598

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Book Description
This book is a collection of best selected research papers presented at the International Conference on Communication and Artificial Intelligence (ICCAI 2020), held in the Department of Electronics & Communication Engineering, GLA University, Mathura, India, during 17–18 September 2020. The primary focus of the book is on the research information related to artificial intelligence, networks, and smart systems applied in the areas of industries, government sectors, and educational institutions worldwide. Diverse themes with a central idea of sustainable networking solutions are discussed in the book. The book presents innovative work by leading academics, researchers, and experts from industry.

Pattern Recognition and Classification in Time Series Data

Pattern Recognition and Classification in Time Series Data PDF Author: Volna, Eva
Publisher: IGI Global
ISBN: 1522505660
Category : Computers
Languages : en
Pages : 295

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Book Description
Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.

Cybernetical Intelligence

Cybernetical Intelligence PDF Author: Kelvin K. L. Wong
Publisher: John Wiley & Sons
ISBN: 139421748X
Category : Computers
Languages : en
Pages : 436

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Book Description
Highly comprehensive, detailed, and up-to-date overview of artificial intelligence and cybernetics, with practical examples and supplementary learning resources Cybernetical Intelligence: Engineering Cybernetics with Machine Intelligence is a comprehensive guide to the field of cybernetics and neural networks, , as well as the mathematical foundations of these technologies. The book provides a detailed explanation of various types of neural networks, including feedforward networks, recurrent neural networks, and convolutional neural networks, and their applications to different real-world problems. This groundbreaking book presents a pioneering exploration of machine learning within the framework of cybernetics. It marks a significant milestone in the field's history, as it is the first book to describe the development of machine learning from a cybernetics perspective. The introduction of the concept of "Cybernetical Intelligence" and the generation of new terminology within this context propel new lines of thought in the historical development of artificial intelligence. With its profound implications and contributions, this book holds immense importance and is poised to become a definitive resource for scholars and researchers in this field of study. Each chapter is specifically designed to introduce the theory with several examples. This comprehensive book includes exercise questions at the end of each chapter, providing readers with valuable opportunities to apply and strengthen their understanding of cybernetical intelligence. To further support the learning journey, solutions to these questions are readily accessible on our book's companion site. Additionally, the companion site offers programming practice exercises and assignments, enabling readers to delve deeper into the practical aspects of the subject matter. Cybernetical Intelligence includes information on: History and development of cybernetics and its influence on the development of neural networks Developments and innovations in artificial intelligence and machine learning, such as deep reinforcement learning, generative adversarial networks, and transfer learning Mathematical foundations of artificial intelligence and cybernetics, including linear algebra, calculus, and probability theory Ethical implications of artificial intelligence and cybernetics, and responsible and transparent development and deployment of AI systems Presenting a highly detailed and comprehensive overview of the field, with modern developments thoroughly discussed, Cybernetical Intelligence is an essential textbook resource that helps students make connections with the real-life engineering problems by providing both theory and practice, along with a myriad of helpful learning aids.

Method of classification of global machine conditions based on spectral features of infrared images and classifiers fusion

Method of classification of global machine conditions based on spectral features of infrared images and classifiers fusion PDF Author: Marek Fidali
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 18

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Book Description
This paper describes an original method of global machine condition assessment for infrared condition monitoring and diagnostics systems. This method integrates two approaches: the first is processing and analysis of infrared images in the frequency domain by the use of 2D Fourier transform and a set of F-image features, the second uses fusion of classification results obtained independently for F-image features. To find the best condition assessment solution, the two different types of classifiers, k-nearest neighbours and support vector machine, as well as data fusion method based on Dezert–Smarandache theory have been investigated. This method has been verified using infrared images recorded during experiments performed on the laboratory model of rotating machinery. The results obtained during the research confirm that the method could be successfully used for the identification of operational conditions that are difficult to be recognised.

Classification and Modeling with Linguistic Information Granules

Classification and Modeling with Linguistic Information Granules PDF Author: Hisao Ishibuchi
Publisher: Springer Science & Business Media
ISBN: 9783540207672
Category : Language Arts & Disciplines
Languages : en
Pages : 328

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Book Description
Many approaches have already been proposed for classification and modeling in the literature. These approaches are usually based on mathematical mod els. Computer systems can easily handle mathematical models even when they are complicated and nonlinear (e.g., neural networks). On the other hand, it is not always easy for human users to intuitively understand mathe matical models even when they are simple and linear. This is because human information processing is based mainly on linguistic knowledge while com puter systems are designed to handle symbolic and numerical information. A large part of our daily communication is based on words. We learn from various media such as books, newspapers, magazines, TV, and the Inter net through words. We also communicate with others through words. While words play a central role in human information processing, linguistic models are not often used in the fields of classification and modeling. If there is no goal other than the maximization of accuracy in classification and model ing, mathematical models may always be preferred to linguistic models. On the other hand, linguistic models may be chosen if emphasis is placed on interpretability.

Advanced Machine Intelligence and Signal Processing

Advanced Machine Intelligence and Signal Processing PDF Author: Deepak Gupta
Publisher: Springer Nature
ISBN: 9811908400
Category : Technology & Engineering
Languages : en
Pages : 859

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Book Description
This book covers the latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing, and their applications in real world. The topics covered in machine learning involve feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modeling from video, 3D object recognition, localization and tracking, medical image analysis, and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multitask, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), and electromyogram (EMG).

Industrial Internet of Things

Industrial Internet of Things PDF Author: Sabina Jeschke
Publisher: Springer
ISBN: 3319425595
Category : Technology & Engineering
Languages : en
Pages : 714

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Book Description
This book develops the core system science needed to enable the development of a complex industrial internet of things/manufacturing cyber-physical systems (IIoT/M-CPS). Gathering contributions from leading experts in the field with years of experience in advancing manufacturing, it fosters a research community committed to advancing research and education in IIoT/M-CPS and to translating applicable science and technology into engineering practice. Presenting the current state of IIoT and the concept of cybermanufacturing, this book is at the nexus of research advances from the engineering and computer and information science domains. Readers will acquire the core system science needed to transform to cybermanufacturing that spans the full spectrum from ideation to physical realization.

Classification and Clustering in Biomedical Signal Processing

Classification and Clustering in Biomedical Signal Processing PDF Author: Dey, Nilanjan
Publisher: IGI Global
ISBN: 152250141X
Category : Technology & Engineering
Languages : en
Pages : 502

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Book Description
Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research findings in the areas of signal processing for biomedical applications with an emphasis on classification and clustering techniques, this essential publication is designed for use by medical professionals, IT developers, and advanced-level graduate students.