Download or read book Learning Human Behavior Influences Robot Labour Needs written by John Lok and published by . This book was released on 2022-09-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In my this book, I shall attempt to explain how and why ecommerce may be one kind network human job as well as how human behavior influence future robot technology need in different kinds of businesses. Thus, it brings these question: Whether (AI) robotic workers can be instead of traditional human workers in these different new markets to bring positive or negative impaction to change human job nature change? Can human behavior influence robotic labor need?

Download or read book Learning How Robots Influence Human Future Behavior written by John Lok and published by . This book was released on 2022-09-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether (AI) robotic workers can be instead of traditional human workers in these different new markets to bring positive or negative impaction to change human job nature change? In recent years, machines had been used to be human's tasks in the performance of certain tasks related to intelligence, such as aspects of image recognition. Experts also forecast that rapid progress in the field of specialized artificial intelligence will continue. Then, it also brings this question: Does (AI) exceed that of human performance on more and more tasks to replace human jobs? If it is truth, will some of human jobs to be disappeared? (AI) will be instead of human some simple jobs, then unemployment rate to the low skillful and low educated workers will be increased. Whether (AI) will be raised either production or performance or unemployment to bring human job market more advantages or more disadvantages? In my this book, I shall explain whether (AI) will bring benefits or disadvantages to human job market. I shall give example to let my readers to think how to support my final view point.

Download or read book Designing Robot Behavior in Human Robot Interactions written by Changliu Liu and published by CRC Press. This book was released on 2019-09-12 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, we have set up a unified analytical framework for various human-robot systems, which involve peer-peer interactions (either space-sharing or time-sharing) or hierarchical interactions. A methodology in designing the robot behavior through control, planning, decision and learning is proposed. In particular, the following topics are discussed in-depth: safety during human-robot interactions, efficiency in real-time robot motion planning, imitation of human behaviors from demonstration, dexterity of robots to adapt to different environments and tasks, cooperation among robots and humans with conflict resolution. These methods are applied in various scenarios, such as human-robot collaborative assembly, robot skill learning from human demonstration, interaction between autonomous and human-driven vehicles, etc. Key Features: Proposes a unified framework to model and analyze human-robot interactions under different modes of interactions. Systematically discusses the control, decision and learning algorithms to enable robots to interact safely with humans in a variety of applications. Presents numerous experimental studies with both industrial collaborative robot arms and autonomous vehicles.

Download or read book Can Robots Influence Human Behavioral Change written by John Lok and published by Notion Press. This book was released on 2022-09-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: How AI technology influence productivities and service performance ? Whether it can raise productivities and improve service performance?This book aims to explain why and how future artificial intelligent technology ( big data gathering method) can be applied to assit businesses to predict why and when and how consumer behavior changes. I shall explain why traditional psychological and statistic and marketing methods are applied to predict consumer behaviors, human's judgement and analytical effort will be worse to compare AI machine's judgement and analytical effort. Also, I shall indicate different business organizations why they apply AI big data gathering method to help them to design any questionnaires ( surveys) questions which will be more valid and useful to conclude human's questionnaires ( surveys) design questions method. This book has these two research questions need to be answered? Can apply (AI) learning machine predict consumer behaviors? Can (AI) learning machine replace human marketing research method, e.g. survey or human psychological and micro and macro economic methods to predict consumer behaviors more accurate? Can robots influence human social future behavioral change?

Download or read book Robot Learning from Human Demonstration written by Sonia Dechter and published by Springer Nature. This book was released on 2022-06-01 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Artificial Intelligence Brings Social Economic written by Johnny Ch LOK and published by . This book was released on 2020-07-29 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: In robots learning process, what difficulties which will face, the scientist indicated this question concerns how to influence robot's learning abilities: Has RL certain desirable qualifties, such as the learning abilities possibility to explore and learn from unsupervised experience? Many also queation RL as a variable technique for learning in complex real-world environments because of practical problems, such as long training time requirements, non-scaling state representations, sparse rewards ( resulting in slow utility propagation) and safe exploration strategies. As a result, reinforcement learning has been utilized for teaching robots and game characters, incorporating real-time human feedback by having a person supply reward and/or punishment as an additional input to the reward function.Consequently, the scientist discovered human's teaching method is the most important factor to influence the robot's learning abilities amonf all other environment factors. He also assumed and argued that reinforcement based learning approaches should be reformulated to move effectively incorporate a human teacher. To do this properly, the educational robot must understand the human teacher's contribution; how does the human teach? and what does the educational robot try to communicate from a robot learner? The scientist suggested human trainers ought use these methods to educate robot learners to learn more easily. His main findings indicates reward factor can influence the human robot teachers' motives to teach robot learners to learn, due to more reward can encourage the human robot trainers to teach robots to learn their knowledge and skill. He also found that robot users read the behavior of the robot machine learners and adjust the human robot trainer whose training strategies as whose mental model of the different robot human trainer education method changes. Viweing the human input as a traditional RL reward signal does not take advantage of the fact that a teacher adjusts hose training behavior to best suit the robot educational learner.In addition to the related RL works mentioned above. Every human robot trainer needs to consider the topic of human input for machine learning systems. Personalization agents and adaptive user interfaces are examples of software that learns by observing human behaviors modeling humann preferences or activities. It empathizes how human teaches the robot learner through interaction, various works address trainable software and robotic agents, exploring explicit human input: learning classification tasks and navigation tasks via natural language, robots that learn by demonstration or/and software agents that learn or training. It seems how to design the robot machine learning software technology will also influence the robot's learning abilities. Thus, human trainer's software learning machine and how to give reward to encourage the human trainer's teaching behavior to let the robot to learn, these factors will influence the robot's learning ability to be applied to education industry to assist human teacher's teaching job successfully. Because how much knowledge and skill, the robot can learn from the human trainer, how much educational knowledge that the robot can own to prepare to teach any students to learn easily. Hence, the human trainer's knowledge and skill will quality to satisfy its primary, secondary and university students learning need.⦁Can robots be teachable agents to students really?

Download or read book The 21st Century Industrial Robot When Tools Become Collaborators written by Maria Isabel Aldinhas Ferreira and published by Springer Nature. This book was released on 2021-10-25 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to discuss the technical and ethical challenges posed by the present technological framework and to highlight the fundamental role played by human-centred design and human factors in the definition of robotic architectures for human–robot collaboration. The book gives an updated overview of the most recent robotic technology, conceived and designed to collaborate with human beings in industrial working scenarios. The technological development of robotics over the last years and the fast evolution of AI, machine learning and IoT have paved the way for applications that extend far beyond the typical use of robots performing repetitive tasks in exclusive spaces. In this new technological paradigm that is expected to drive the robotics market in the coming years, robots and workers will coexist in the same workplace, sharing not only this lived space, but also the roles and functions inherent to a process of production, merging the benefits of automated and manual performing. However, having robots cooperating in real time with workers, responding in a physical, psychological and social adequate way, requires a human-centred design that not only calls for high safety standards regulating the quality of human–robot interaction, but also demands the robot's fine-grained perception and awareness of the dynamics of its surrounding environment, namely the behaviours of their human peers—their expected actions/responses—fostering the necessary collaborative efforts towards the accomplishment of the tasks to be executed.

Download or read book Learning and Control for Interactions in Mixed Human robot Environments written by Wilko Schwarting and published by . This book was released on 2021 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: Autonomous robots will soon be a commonplace presence in our daily lives in environments such as homes, factories, and roads. In order to reap the tremendous benefits that these robots offer to society, we must ensure that they can interact with humans seamlessly and safely. In this dissertation, we study intelligent agents that learn how to reason about human behavior and people's intentions. These agents predict others' intentions and implicitly communicate their own intentions through human-like actions that can be understood by people. They also anticipate and leverage the effect of their actions on the actions of others in the environment. When their own interests and the interests of others are not aligned, the agents quantify people's willingness to cooperate or defect and negotiate through social behavior. The agents form beliefs by perceiving the world and the actions of others. They create plans to actively gather information about themselves, others, and the environment, while simultaneously avoiding actions that lead to high uncertainty. They also reason about the beliefs of others, and can leverage how their actions influence others' beliefs. In part (I) of this thesis, we formulate social human-robot interactions between agents as a best-response game wherein each agent negotiates to maximize their utility, and learn human rewards from data. We measure Social Value Orientation (SVO) to quantify an agent's degree of selfishness or altruism to better predict human behavior. In part (II) we additionally enable agents to leverage information gain and reasoning about the beliefs of others in stochastic environments with partial observations by combining game-theoretic and belief-space planning. In part (III) we present a multi-agent reinforcement learning algorithm that learns competitive visual control policies through self-play in imagination. The agent learns from competition by imagining multi-agent interaction sequences in the compact latent space of a learned world model that combines a joint transition function with opponent viewpoint prediction. Lastly, in part (IV) we introduce Parallel Autonomy, a Guardian system that uses uncertain predictions to provide safety in challenging driving scenarios while following people's desired actions as close as safely possible.

Download or read book Learning Human Behavior How Influences Technologic Innovation written by John Lok and published by . This book was released on 2022-09-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: How social change influences human behavioral change ? Why human behavior may be influenced by social change? Our individual behavior whether can be influenced to bring negative or positive attitude by social change? I shall attempt to indicate cases to explain whether our individual behavior can be influenced to changed by social environment change. Readers can have more understand how and why social change may influence our behavior in possible. Behavioral economy is one useful and fun social subject. Behavioral economists ususally research how and why human behaviors may influence economy growth or recession, or how and why economy environment changing factor may influence human behavior changes. Why do our societies need to innovate? Product innovation, medical technology innovation, space technology innovation, transport service innovation, educational innovation. I shall concentrate on discuss these several aspects. If our societies can not be innovated on above several aspect, then what negative impact may bring to influence our societies. I shall attempt to indicate some evidences to explain what negative impact will cause if our future societies can not innovate to above several aspects in success. I hope my readers can make personal judgement whether my analysis and opinion is right or wrong as well as you can discuss your opinion to argue my view point after you read this book.

Download or read book Learning Robot Interactive Behaviors in Presence of Humans and Groups of Humans written by Omar Adair Islas Ramírez and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past years, robots have been a part of our every day lives. Even when we do not see them, we depend on them to build our computers, mobile phones, cars and more. They are also been used for organizing stocks in warehouses. And, with the growth of autonomous cars, we see them driving autonomously on highways and cities. Another area of growth is social robotics. We can see a lot of studies such as robots helping children with autism. Other robots are being used to receive people in hotels or to interact with people in shopping centers. In the latter examples, robots need to understand people behavior. In addition, in the case of mobile robots, they need to know how to navigate in human environments. In the context of human environments, this thesis explores socially acceptable navigation of robots towards people. To give an example, when a robot approaches one person, the robot shall by no means treat people as an obstacle because the robot get really close to the human and interfere with her personal space. The human is an entity that needs to be considered based on social norms that we (humans) use on a daily basis. In a first time, we explore how a robot can approach one person. A person is an entity that can be bothered if someone or something approaches invading her personal space. The person also will feel distressed when she is approached from behind. These social norms have to be respected by the robot. For this reason, we decided to model the behavior of the robot through learning algorithms. We manually approach a robot to a person several times and the robot learns how to reproduce this behavior. In a second time, we present how a robot can understand what is a group of people. We, humans, have the ability to do this intuitively. However, for a robot, a mathematical model is essential. Lastly, we address how a robot can approach a group of people. We use exemplary demonstrations to teach this behavior to the robot. We evaluate then the robot's movements by for example, observing if the robot invades people's personal space during the trajectory.

Download or read book Trust in Human Robot Interaction written by Chang S. Nam and published by Academic Press. This book was released on 2020-11-17 with total page 614 pages. Available in PDF, EPUB and Kindle. Book excerpt: Trust in Human-Robot Interaction addresses the gamut of factors that influence trust of robotic systems. The book presents the theory, fundamentals, techniques and diverse applications of the behavioral, cognitive and neural mechanisms of trust in human-robot interaction, covering topics like individual differences, transparency, communication, physical design, privacy and ethics. Presents a repository of the open questions and challenges in trust in HRI Includes contributions from many disciplines participating in HRI research, including psychology, neuroscience, sociology, engineering and computer science Examines human information processing as a foundation for understanding HRI Details the methods and techniques used to test and quantify trust in HRI

Download or read book Groups Leadership and Men written by United States. Office of Naval Research and published by . This book was released on 1951 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Human Factors in Robots Drones and Unmanned Systems written by Alexandra Medina-Borja and published by AHFE Conference. This book was released on 2024-07-24 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the 15th International Conference on Applied Human Factors and Ergonomics and the Affiliated Conferences, Nice, France, 24-27 July 2024.

Download or read book How Robotic Brings Positive Or Negative Impact to Global Labor and Business Market written by Johnny Ch Lok and published by . This book was released on 2020-09-06 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part OneLabor market behavioral changeChapter 5(AI) -driven automation industry development1.1(AI) - driven automation industry development how to influence work nature change(AI) -driven automation industry will create wealth and expand economy growth to any countries, but it will be accompanied by changed in the skills that workers need to learn. One of main ways that technology increases productivity is by decreasing the number of labor hours needed to create a unit of output. It implies (AI) technology will influence low educated and low skillful labor number to be decreased ( reduction employment number).In contrast, technological change tended to work in a different direction throughout the nowadays. The advance of computer and the internet raised the relative productivity of higher skilled workers. So, routine-intensive occupations that focused on predictable tasks disappearance, such as switch board, operators, filming checkers, travel agents and assembling line workers etc. were particularly replaced by new technologies.However, today, it may be challenging to predict exactly which jobs will be most immediately affected by (AI) driven-automation. The reason is because (AI) is not a single technology, but rather a collection of technologies that are felt unevenly through the economy to influence job changing both negatively and positively. In positively view point, (AI) driven-automation will make many workers more productive and increase demand for certain skills. Consequently, new jobs are likely to be directly create in areas, such as the development and supervision of (AI) as well as indirectly created in a range of areas throughout the economy as higher incomes lead to expanded demand. Otherwise, in negatively view point, many traditional human needed ( demand) skillful jobs will be threatened by automation are highly concentrated among lower-paid, lower-skilled and less -educated workers. It means automation will cause pressure on demand for this group, pressure and employment, if (AI) can replace the low skilled and less educated workers' jobs. Thus, (AI) will have negative influence to impact on the labor market.(AI) capabilities will enable automation of some tasks that have long required human labor. Why can (AI) replace some simple human jobs? For example, advances in robotics are expanding machines' abilities to interact with and sharp the physical world. Combined, (AI) and robotics will give rise to smarter machines that can perform more sophisticated functions than ever before and brings more advantages that humans have exercised. This will permit automation of many tasks now performed by human workers and could change the shape of the labor market and human activity.1.2How (AI) influences labor marketToday, it may be challenging to predict exactly which jobs will be most immediately affected by (AI)-driven automation. Because (AI) is not a single technology, but rather a collection of technologies that are applied to specific tasks.Some specific predictions are possible based on the current (AI) technology. For example, driving jobs and house cleaning jobs, bank counter service jobs, telephone enquiry service operators. Restaurant cooking jobs, simple accounting record service jobs etc. that require relatively less education to perform. Advancements in computer vision and related technologies have made the feasibility of fully appear more likely, potentially displacing some workers in driving-dominant professions. Seemingly similar robot, for which the operational tasks is less specific of navigating to a specific destination when following a set of given rules and preserving safety.

Download or read book Emerging Needs and Opportunities for Human Factors Research written by National Research Council and published by National Academies Press. This book was released on 1995-10-15 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book identifies areas that represent new needs and opportunities for human factors research in the coming decades. It is forward-looking, problem oriented, and selectively focused on national or global problems, including productivity in organizations, education and training, employment and disabilities, health care, and environmental change; technology issues, including communications technology and telenetworking, information access and usability, emerging technologies, automation, and flexible manufacturing, and advanced transportation systems; and human performance, including cognitive performance under stress and aiding intellectual work.

Download or read book Learning to Adapt for Intelligent Robot Behavior written by Mengxi Li and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of robotics has been rapidly evolving in recent years, and robots are being used in an ever-increasing number of applications, from manufacturing to healthcare to household chores. One of the key challenges in robotics is enabling robots to perform complex manipulation tasks in unstructured and dynamic environments. While there have been significant advances in robot learning and control, many existing approaches are limited by their reliance on pre-defined motion primitives or generic models that do not account for the specific characteristics of individual users, other cooperative agents or the interacting objects. In order to be effective in these various settings, robots need to be able to adapt to different tasks and environments, and to interact with different types of agents, such as humans and other robots. This thesis investigates learning approaches for enabling robots to adapt their behavior in order to achieve intelligent robot behavior. In the first part of this thesis, we focus on enabling robots to better adapt to humans. We start by exploring how to leverage different sources of data to achieve personalization for human users. Firstly, we investigate how humans prefer to teleoperate assistive robot arms using low-dimensional controllers, such as joysticks. We present an algorithm that can efficiently develop personalized control for assistive robots. Here the data is obtained by initially demonstrating the behavior of the robot and then query the user to collect their corresponding preferred teleoperation control input from the joysticks. Subsequently, we delve into the exploration of leveraging weaker signals to infer information from agents, such as physical corrections. Experiment results indicate that human corrections are correlated and reasoning over these corrections together achieves improved accuracy. Finally, instead of only adapting to a single human user, we investigate how robots can more efficiently cooperate with and influence human teams by reasoning and exploiting the team structure. We apply our framework to two types of group dynamics, leading-following and predator-prey, and demonstrate that robots can first develop a group representation and utilize this representation to successfully influence a group to achieve various goals. In the second part of this thesis, we extend our investigation from human users to robot agents. We tackle the problem of how decentralized robot teams can adapt to each other by observing only the actions of other agents. We identify the problem of an infinite reasoning loop within the team and propose a solution by assigning different roles, such as "speaker" and "listener, " to the robot agents. This approach enables us to treat observed actions as a communication channel, thereby achieving effective collaboration within the decentralized team. Moving on to the third part of this thesis, we explore the topic of adapting to different tasks by developing customized tools. We emphasize the critical role of tools in determining how a robot interacts with objects, making them important in customizing robots for specific tasks. To address this, we present an end-to-end framework to automatically learn tool morphology for contact-rich manipulation tasks by leveraging differentiable physics simulators. Finally, we conclude the thesis by summarizing our efforts and discussing future directions.

Download or read book NASA SP 7500 written by United States. National Aeronautics and Space Administration and published by . This book was released on 1982 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: