Robot Learning From Human Teachers
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Robot Learning From Human Teachers
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Author : Sonia Chernova
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2014-04-01
Robot Learning From Human Teachers written by Sonia Chernova and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-01 with Computers categories.
Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.
Robot Learning From Human Teachers
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Author : Sonia Chernova
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Robot Learning From Human Teachers written by Sonia Chernova and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.
Should Robots Replace Teachers
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Author : Neil Selwyn
language : en
Publisher: Polity
Release Date : 2019-11-04
Should Robots Replace Teachers written by Neil Selwyn and has been published by Polity this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-04 with Social Science categories.
Developments in AI, robotics and big data are changing the nature of education. Yet the implications of these technologies for the teaching profession are uncertain. While most educators remain convinced of the need for human teachers, outside the profession there is growing anticipation of a technological reinvention of the ways in which teaching and learning take place. Through an examination of technological developments such as autonomous classroom robots, intelligent tutoring systems, learning analytics and automated decision-making, Neil Selwyn highlights the need for nuanced discussions around the capacity of AI to replicate the social, emotional and cognitive qualities of human teachers. He pushes conversations about AI and education into the realm of values, judgements and politics, ultimately arguing that the integration of any technology into society must be presented as a choice. Should Robots Replace Teachers? is a must-read for anyone interested in the future of education and work in our increasingly automated times.
Human In The Loop Robot Control And Learning
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Author : Luka Peternel
language : en
Publisher: Frontiers Media SA
Release Date : 2020-01-22
Human In The Loop Robot Control And Learning written by Luka Peternel 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 2020-01-22 with categories.
In the past years there has been considerable effort to move robots from industrial environments to our daily lives where they can collaborate and interact with humans to improve our life quality. One of the key challenges in this direction is to make a suitable robot control system that can adapt to humans and interactively learn from humans to facilitate the efficient and safe co-existence of the two. The applications of such robotic systems include: service robotics and physical human-robot collaboration, assistive and rehabilitation robotics, semi-autonomous cars, etc. To achieve the goal of integrating robotic systems into these applications, several important research directions must be explored. One such direction is the study of skill transfer, where a human operator’s skilled executions are used to obtain an autonomous controller. Another important direction is shared control, where a robotic controller and humans control the same body, tool, mechanism, car, etc. Shared control, in turn invokes very rich research questions such as co-adaptation between the human and the robot, where the two agents can benefit from each other’s skills or must adapt to each other’s behavior to achieve effective cooperative task executions. The aim of this Research Topic is to help bridge the gap between the state-of-the-art and above-mentioned goals through novel multidisciplinary approaches in human-in-the-loop robot control and learning.
Robot Learning By Visual Observation
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Author : Aleksandar Vakanski
language : en
Publisher: John Wiley & Sons
Release Date : 2017-01-13
Robot Learning By Visual Observation written by Aleksandar Vakanski and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-13 with Technology & Engineering categories.
This book presents programming by demonstration for robot learning from observations with a focus on the trajectory level of task abstraction Discusses methods for optimization of task reproduction, such as reformulation of task planning as a constrained optimization problem Focuses on regression approaches, such as Gaussian mixture regression, spline regression, and locally weighted regression Concentrates on the use of vision sensors for capturing motions and actions during task demonstration by a human task expert
Cross Modal Learning Adaptivity Prediction And Interaction
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Author : Jianwei Zhang
language : en
Publisher: Frontiers Media SA
Release Date : 2023-02-02
Cross Modal Learning Adaptivity Prediction And Interaction written by Jianwei Zhang 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 2023-02-02 with Science categories.
The purpose of this Research Topic is to reflect and discuss links between neuroscience, psychology, computer science and robotics with regards to the topic of cross-modal learning which has, in recent years, emerged as a new area of interdisciplinary research. The term cross-modal learning refers to the synergistic synthesis of information from multiple sensory modalities such that the learning that occurs within any individual sensory modality can be enhanced with information from one or more other modalities. Cross-modal learning is a crucial component of adaptive behavior in a continuously changing world, and examples are ubiquitous, such as: learning to grasp and manipulate objects; learning to walk; learning to read and write; learning to understand language and its referents; etc. In all these examples, visual, auditory, somatosensory or other modalities have to be integrated, and learning must be cross-modal. In fact, the broad range of acquired human skills are cross-modal, and many of the most advanced human capabilities, such as those involved in social cognition, require learning from the richest combinations of cross-modal information. In contrast, even the very best systems in Artificial Intelligence (AI) and robotics have taken only tiny steps in this direction. Building a system that composes a global perspective from multiple distinct sources, types of data, and sensory modalities is a grand challenge of AI, yet it is specific enough that it can be studied quite rigorously and in such detail that the prospect for deep insights into these mechanisms is quite plausible in the near term. Cross-modal learning is a broad, interdisciplinary topic that has not yet coalesced into a single, unified field. Instead, there are many separate fields, each tackling the concerns of cross-modal learning from its own perspective, with currently little overlap. We anticipate an accelerating trend towards integration of these areas and we intend to contribute to that integration. By focusing on cross-modal learning, the proposed Research Topic can bring together recent progress in artificial intelligence, robotics, psychology and neuroscience.
Hhai 2023 Augmenting Human Intellect
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Author : P. Lukowicz
language : en
Publisher: IOS Press
Release Date : 2023-07-07
Hhai 2023 Augmenting Human Intellect written by P. Lukowicz and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-07 with Computers categories.
Artificial intelligence (AI) has been much in the news recently, with some commentators expressing concern that AI might eventually replace humans. But many developments in AI are designed to enhance and supplement the performance of humans rather than replace them, and a novel field of study, with new approaches and solutions to the development of AI, has arisen to focus on this aspect of the technology. This book presents the proceedings of HHAI2023, the 2nd International Conference on Hybrid Human-Artificial Intelligence, held from 26-30 June 2023, in Munich, Germany. The HHAI international conference series is focused on the study of artificially intelligent systems that cooperate synergistically, proactively, responsibly and purposefully with humans, amplifying rather than replacing human intelligence, and invites contributions from various fields, including AI, human-computer interaction, the cognitive and social sciences, computer science, philosophy, among others. A total of 78 submissions were received for the main conference track, and most papers were reviewed by at least three reviewers. The overall final acceptance rate was 43%, with 14 contributions accepted as full papers, 14 as working papers, and 6 as extended abstracts. The papers presented here cover topics including interactive hybrid agents; hybrid intelligence for decision support; hybrid intelligence for health; and values such as fairness and trust in hybrid intelligence. We further accepted 17 posters and 4 demos as well as 8 students to the first HHAI doctoral consortium this year. The authors of 4 working papers and 2 doctoral consortium submissions opted for not publishing their submissions to allow a later full submission, resulting in a total of 57 papers included in this proceedings Addressing all aspects of AI systems that assist humans and emphasizing the need for adaptive, collaborative, responsible, interactive, and human-centered artificial intelligence systems which can leverage human strengths and compensate for human weaknesses while considering social, ethical, and legal considerations, the book will be of interest to all those working in the field.
Trust In Robots
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Author : Sabine T. Koeszegi
language : en
Publisher: TU Wien Academic Press
Release Date : 2022-12-15
Trust In Robots written by Sabine T. Koeszegi and has been published by TU Wien Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-15 with Technology & Engineering categories.
Robots are increasingly becoming prevalent in our daily lives within our living or working spaces. We hope that robots will take up tedious, mundane or dirty chores and make our lives more comfortable, easy and enjoyable by providing companionship and care. However, robots may pose a threat to human privacy, safety and autonomy; therefore, it is necessary to have constant control over the developing technology to ensure the benevolent intentions and safety of autonomous systems. Building trust in (autonomous) robotic systems is thus necessary. The title of this book highlights this challenge: “Trust in robots—Trusting robots”. Herein, various notions and research areas associated with robots are unified. The theme “Trust in robots” addresses the development of technology that is trustworthy for users; “Trusting robots” focuses on building a trusting relationship with robots, furthering previous research. These themes and topics are at the core of the PhD program “Trust Robots” at TU Wien, Austria.
Social Robotics
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Author : Miguel A. Salichs
language : en
Publisher: Springer Nature
Release Date : 2019-11-21
Social Robotics written by Miguel A. Salichs and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-21 with Computers categories.
This book constitutes the refereed proceedings of the 11th International Conference on Social Robotics, ICSR 2019, held in Madrid, Spain, in November 2019.The 69 full papers presented were carefully reviewed and selected from 92 submissions. The theme of the 2018 conference is: Friendly Robotics.The papers focus on the following topics: perceptions and expectations of social robots; cognition and social values for social robots; verbal interaction with social robots; social cues and design of social robots; emotional and expressive interaction with social robots; collaborative SR and SR at the workplace; game approaches and applications to HRI; applications in health domain; robots at home and at public spaces; robots in education; technical innovations in social robotics; and privacy and safety of the social robots.
Social Robotics
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Author : Filippo Cavallo
language : en
Publisher: Springer Nature
Release Date : 2023-02-01
Social Robotics written by Filippo Cavallo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-01 with Computers categories.
The two-volume set LNAI 13817 and 13818 constitutes the refereed proceedings of the 14th International Conference on Social Robotics, ICSR 2022, which took place in Florence, Italy, in December 2022. The 111 papers presented in the proceedings set were carefully reviewed and selected from 143 submissions. The contributions were organized in topical sections as follows: Social robot navigation and interaction capabilities (voice, tactile); Social robot perception and control capabilities; Investigating non verbal interaction with Social robots; Foster attention and engagement strategies in social robots; Special Session 1: Social Robotics Driven by Intelligent Perception and Endogenous Emotion-Motivation Core; Special Session 2: Adaptive behavioral models of robotic systems based on brain-inspired AI cognitive architectures; Advanced HRI capabilities for interacting with children; Social robots as advanced educational tool; Social robot applications in clinical and assistive scenarios; Collaborative social robots through dynamic game; Design and evaluate user’s robot perception and acceptance; Ethics, gender & trust in social robotics.