Robust Artificial Intelligence For Neurorobotics

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Robust Artificial Intelligence For Neurorobotics

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Author : Subramanian Ramamoorthy
language : en
Publisher: Frontiers Media SA
Release Date : 2022-01-31

Robust Artificial Intelligence For Neurorobotics written by Subramanian Ramamoorthy and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-31 with Science categories.

Robust Intelligence And Trust In Autonomous Systems

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Author : Ranjeev Mittu
language : en
Publisher: Springer
Release Date : 2016-04-07

Robust Intelligence And Trust In Autonomous Systems written by Ranjeev Mittu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-07 with Computers categories.

This volume explores the intersection of robust intelligence (RI) and trust in autonomous systems across multiple contexts among autonomous hybrid systems, where hybrids are arbitrary combinations of humans, machines and robots. To better understand the relationships between artificial intelligence (AI) and RI in a way that promotes trust between autonomous systems and human users, this book explores the underlying theory, mathematics, computational models, and field applications. It uniquely unifies the fields of RI and trust and frames it in a broader context, namely the effective integration of human-autonomous systems. A description of the current state of the art in RI and trust introduces the research work in this area. With this foundation, the chapters further elaborate on key research areas and gaps that are at the heart of effective human-systems integration, including workload management, human computer interfaces, team integration and performance, advanced analytics, behavior modeling, training, and, lastly, test and evaluation. Written by international leading researchers from across the field of autonomous systems research, Robust Intelligence and Trust in Autonomous Systems dedicates itself to thoroughly examining the challenges and trends of systems that exhibit RI, the fundamental implications of RI in developing trusted relationships with present and future autonomous systems, and the effective human systems integration that must result for trust to be sustained. Contributing authors: David W. Aha, Jenny Burke, Joseph Coyne, M.L. Cummings, Munjal Desai, Michael Drinkwater, Jill L. Drury, Michael W. Floyd, Fei Gao, Vladimir Gontar, Ayanna M. Howard, Mo Jamshidi, W.F. Lawless, Kapil Madathil, Ranjeev Mittu, Arezou Moussavi, Gari Palmer, Paul Robinette, Behzad Sadrfaridpour, Hamed Saeidi, Kristin E. Schaefer, Anne Selwyn, Ciara Sibley, Donald A. Sofge, Erin Solovey, Aaron Steinfeld, Barney Tannahill, Gavin Taylor, Alan R. Wagner, Yue Wang, Holly A. Yanco, Dan Zwillinger.

Advances In Climbing And Walking Robots

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Author : Ming Xie
language : en
Publisher:
Release Date : 2007

Advances In Climbing And Walking Robots written by Ming Xie and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.

Robotics is an exciting field in engineering and natural sciences. Robotics has already made a significant contribution to many industries with the widespread use of industrial robots for tasks such as assembly, welding, painting, and handling materials. In parallel, we have witnessed the emergence of special robots which can undertake assistive jobs, such as search and rescue, de-mining, surveillance, exploration, and security functions. Indeed, the interest in mobile machines, such as climbing and walking robots, has broadened the scope of investigation in robotics. This volume covers broad topics related to mobile machines in general, and climbing and walking robots in particular. Papers from the following keynote speakers are included: Heinz Worn (University of Karlsruhe, Germany), Atsuo Takanishi (University of Waseda, Japan), John Billingsley (University of Southern Queensland, Australia), Bryan Bridge (London South Bank University, UK) and Neville Hogan (Massachusetts Institute of Technology, USA).

Index To Theses With Abstracts Accepted For Higher Degrees By The Universities Of Great Britain And Ireland And The Council For National Academic Awards

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Author :
language : en
Publisher:
Release Date : 2001

Index To Theses With Abstracts Accepted For Higher Degrees By The Universities Of Great Britain And Ireland And The Council For National Academic Awards written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Dissertations, Academic categories.

Theses on any subject submitted by the academic libraries in the UK and Ireland.

Neurorobotics Explores Machine Learning

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Author : Fei Chen
language : en
Publisher: Frontiers Media SA
Release Date : 2023-01-20

Neurorobotics Explores Machine Learning written by Fei Chen and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Science categories.

Robot Intelligence Technology And Applications 7

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Author : Jun Jo
language : en
Publisher: Springer Nature
Release Date : 2023-02-28

Robot Intelligence Technology And Applications 7 written by Jun Jo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-28 with Technology & Engineering categories.

We are starting to enter a post-COVID-19 life. While this pandemic has made everyone’s life challenging, it also expedited the transition of our everyday lives into a new form, often called “The New Normal.” Although many people often use the terminology, perhaps we still do not have consensus about what it is and what it should be like. However, one thing that is clear namely that robotics and artificial intelligence technologies are playing a critical role in this transition phase of our everyday lives. We saw the emergence of last-mile delivery robots on the street, AI-embedded service robots in restaurants, uninhabited shops, non-face-to-face medical services, conferences and talks in metaverses, and AI-based online education programs. This book is an edition that aims at serving researchers and practitioners in related fields with a timely dissemination of the recent progress in the areas of robotics and artificial intelligence. This book is based on a collection of papers presented at the 10th International Conference on Robot Intelligence Technology and Applications (RiTA), held at Griffith University in the Gold Coast, Queensland, Australia. The conference was held in a hybrid format on December 7–9, 2022, with the main theme “Artificial, Agile, Acute Robot Intelligence.” For better readability, the total of 41 papers are grouped into five chapters: Chapter I: Motion Planning and Control; Chapter II: Vision and Image Processing; Chapter III: Unmanned Aerial Vehicles and Autonomous Vehicles; Chapter IV: Learning and Classification; and Chapter V: Environmental and Societal Robotic Applications. The articles were accepted through a rigorous peer-review process and presented at the RiTA 2022 conference. Also, they were updated, and final versions of the manuscripts were produced after in-depth discussions during the conference. We would like to thank all the authors and editors for contributing to this edition.

Robust Latent Feature Learning For Incomplete Big Data

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Author : Di Wu
language : en
Publisher: Springer Nature
Release Date : 2022-12-06

Robust Latent Feature Learning For Incomplete Big Data written by Di Wu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-06 with Computers categories.

Incomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature analysis (LFA) is one of the most popular representation learning methods tailored for incomplete big data due to its high accuracy, computational efficiency, and ease of scalability. The crux of analyzing incomplete big data lies in addressing the uncertainty problem caused by their incomplete characteristics. However, existing LFA methods do not fully consider such uncertainty. In this book, the author introduces several robust latent feature learning methods to address such uncertainty for effectively and efficiently analyzing incomplete big data, including robust latent feature learning based on smooth L1-norm, improving robustness of latent feature learning using L1-norm, improving robustness of latent feature learning using double-space, data-characteristic-aware latent feature learning, posterior-neighborhood-regularized latent feature learning, and generalized deep latent feature learning. Readers can obtain an overview of the challenges of analyzing incomplete big data and how to employ latent feature learning to build a robust model to analyze incomplete big data. In addition, this book provides several algorithms and real application cases, which can help students, researchers, and professionals easily build their models to analyze incomplete big data.

Artificial Intelligence In Wireless Robotics

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Author : Kwang-Cheng Chen
language : en
Publisher: CRC Press
Release Date : 2022-09-01

Artificial Intelligence In Wireless Robotics written by Kwang-Cheng Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-01 with Computers categories.

Robots, autonomous vehicles, unmanned aerial vehicles, and smart factory, will significantly change human living style in digital society. Artificial Intelligence in Wireless Robotics introduces how wireless communications and networking technology enhances facilitation of artificial intelligence in robotics, which bridges basic multi-disciplinary knowledge among artificial intelligence, wireless communications, computing, and control in robotics. A unique aspect of the book is to introduce applying communication and signal processing techniques to enhance traditional artificial intelligence in robotics and multi-agent systems. The technical contents of this book include fundamental knowledge in robotics, cyber-physical systems, artificial intelligence, statistical decision and Markov decision process, reinforcement learning, state estimation, localization, computer vision and multi-modal data fusion, robot planning, multi-agent systems, networked multi-agent systems, security and robustness of networked robots, and ultra-reliable and low-latency machine-to-machine networking. Examples and exercises are provided for easy and effective comprehension. Engineers wishing to extend knowledge in the robotics, AI, and wireless communications, would be benefited from this book. In the meantime, the book is ready as a textbook for senior undergraduate students or first-year graduate students in electrical engineering, computer engineering, computer science, and general engineering students. The readers of this book shall have basic knowledge in undergraduate probability and linear algebra, and basic programming capability, in order to enjoy deep reading.

Toward Learning Robots

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Author : Walter Van de Velde
language : en
Publisher: MIT Press
Release Date : 1993

Toward Learning Robots written by Walter Van de Velde and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Computers categories.

The contributions in Toward Learning Robots address the question of how a robot can be designed to acquire autonomously whatever it needs to realize adequate behavior in a complex environment. In-depth discussions of issues, techniques, and experiments in machine learning focus on improving ease of programming and enhancing robustness in unpredictable and changing environments, given limitations of time and resources available to researchers. The authors show practical progress toward a useful set of abstractions and techniques to describe and automate various aspects of learning in autonomous systems. The close interaction of such a system with the world reveals opportunities for new architectures and learning scenarios and for grounding symbolic representations, though such thorny problems as noise, choice of language, abstraction level of representation, and operationality have to be faced head-on. Contents Introduction: Toward Learning Robots * Learning Reliable Manipulation Strategies without Initial Physical Models * Learning by an Autonomous Agent in the Pushing Domain * A Cost-Sensitive Machine Learning Method for the Approach and Recognize Task * A Robot Exploration and Mapping Strategy Based on a Semantic Hierarchy of Spatial Representations * Understanding Object Motion: Recognition, Learning and Spatiotemporal Reasoning * Learning How to Plan * Robo-Soar: An Integration of External Interaction, Planning, and Learning Using Soar * Foundations of Learning in Autonomous Agents * Prior Knowledge and Autonomous Learning

Artificial Neural Networks And Machine Learning Icann 2024

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Author : Michael Wand
language : en
Publisher: Springer Nature
Release Date : 2024-09-16

Artificial Neural Networks And Machine Learning Icann 2024 written by Michael Wand and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-16 with Computers categories.

The ten-volume set LNCS 15016-15025 constitutes the refereed proceedings of the 33rd International Conference on Artificial Neural Networks and Machine Learning, ICANN 2024, held in Lugano, Switzerland, during September 17–20, 2024. The 294 full papers and 16 short papers included in these proceedings were carefully reviewed and selected from 764 submissions. The papers cover the following topics: Part I - theory of neural networks and machine learning; novel methods in machine learning; novel neural architectures; neural architecture search; self-organization; neural processes; novel architectures for computer vision; and fairness in machine learning. Part II - computer vision: classification; computer vision: object detection; computer vision: security and adversarial attacks; computer vision: image enhancement; and computer vision: 3D methods. Part III - computer vision: anomaly detection; computer vision: segmentation; computer vision: pose estimation and tracking; computer vision: video processing; computer vision: generative methods; and topics in computer vision. Part IV - brain-inspired computing; cognitive and computational neuroscience; explainable artificial intelligence; robotics; and reinforcement learning. Part V - graph neural networks; and large language models. Part VI - multimodality; federated learning; and time series processing. Part VII - speech processing; natural language processing; and language modeling. Part VIII - biosignal processing in medicine and physiology; and medical image processing. Part IX - human-computer interfaces; recommender systems; environment and climate; city planning; machine learning in engineering and industry; applications in finance; artificial intelligence in education; social network analysis; artificial intelligence and music; and software security. Part X - workshop: AI in drug discovery; workshop: reservoir computing; special session: accuracy, stability, and robustness in deep neural networks; special session: neurorobotics; and special session: spiking neural networks.