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Learning How Robots Influence Human Future Behavior
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Book Synopsis Learning How Robots Influence Human Future Behavior by : John Lok
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.
Book Synopsis Learning Human Behavior Influences Robot Labour Needs by : John Lok
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?
Book Synopsis Can Robots Influence Human Behavioral Change by : John Lok
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 Future Robots written by Domenico Parisi and published by John Benjamins Publishing Company. This book was released on 2014-06-15 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for both robot builders and scientists who study human behaviour and human societies. Scientists do not only collect empirical data but they also formulate theories to explain the data. Theories of human behaviour and human societies are traditionally expressed in words but, today, with the advent of the computer they can also be expressed by constructing computer-based artefacts. If the artefacts do what human beings do, the theory/blueprint that has been used to construct the artefacts explains human behaviour and human societies. Since human beings are primarily bodies, the artefacts must be robots, and human robots must progressively reproduce all we know about human beings and their societies. And, although they are purely scientific tools, they can have one very important practical application: helping human beings to better understand the many difficult problems they face today and will face in the future - and, perhaps, to find solutions for these problems.
Book Synopsis Trust in Human-Robot Interaction by : Chang S. Nam
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
Book Synopsis How to Grow a Robot by : Mark H. Lee
Download or read book How to Grow a Robot written by Mark H. Lee and published by MIT Press. This book was released on 2020-04-28 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to develop robots that will be more like humans and less like computers, more social than machine-like, and more playful and less programmed. Most robots are not very friendly. They vacuum the rug, mow the lawn, dispose of bombs, even perform surgery—but they aren't good conversationalists. It's difficult to make eye contact. If the future promises more human-robot collaboration in both work and play, wouldn't it be better if the robots were less mechanical and more social? In How to Grow a Robot, Mark Lee explores how robots can be more human-like, friendly, and engaging. Developments in artificial intelligence—notably Deep Learning—are widely seen as the foundation on which our robot future will be built. These advances have already brought us self-driving cars and chess match–winning algorithms. But, Lee writes, we need robots that are perceptive, animated, and responsive—more like humans and less like computers, more social than machine-like, and more playful and less programmed. The way to achieve this, he argues, is to “grow” a robot so that it learns from experience—just as infants do. After describing “what's wrong with artificial intelligence” (one key shortcoming: it's not embodied), Lee presents a different approach to building human-like robots: developmental robotics, inspired by developmental psychology and its accounts of early infant behavior. He describes his own experiments with the iCub humanoid robot and its development from newborn helplessness to ability levels equal to a nine-month-old, explaining how the iCub learns from its own experiences. AI robots are designed to know humans as objects; developmental robots will learn empathy. Developmental robots, with an internal model of “self,” will be better interactive partners with humans. That is the kind of future technology we should work toward.
Book Synopsis Robot How Any Why Influences Global Future Labor and Consumer Both Markets Change by : Johnny Ch Lok
Download or read book Robot How Any Why Influences Global Future Labor and Consumer Both Markets Change written by Johnny Ch Lok and published by . This book was released on 2020-11-22 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: -Can (AI) impact human job nature?Human need concern this question: Will artificial intelligence (AI) reduce some human jobs in order to instead of replacing machines to do? Due to artificial intelligence is the ability of machines to do thing, that people would require intelligence. For example, artificial intelligence machine man driving( self-driver), it (AI) machine man driving research is an attempt to discover and describe aspects of human intelligence that can be simulated by driving machine functions. Alternatively, (AI) mathematical research may be another viewed as an attempt to develop a mathematical theory function to describe the abilities and actions of things ( natural or man-made) exhibiting intelligent behavior and server as a design of intelligent calculation machine function.Why do humans need artificial intelligence machines to instead of traditional human service job? For example, can artificial intelligence machine man (self-driving) driver drive to replace human driver? I shall compare the differences between humans and computers: The characteristics of humans are good at recognizing various things, either seen before or not, recognizing the relationship patterns between things. Human thinking is common sense reasoning, combining all types of sensory input, acting appropriately in novel situations, learning new things and changing behavior patterns, making decisions, even when given incomplete information, working with noisy, incomplete information gathering behaviors . However, characteristics of computers are good at: The tasks humans do naturally are extremely difficult for a computer program as intelligent, which must be able to do the same kind of tack as humans do naturally.Hence, (AI) is an combination of many different success and technologies: Linguistics - computational and socio, philosophy-logic, philosophy of mind and of language, electronical engineering -image and speech processing, pattern recognition, robotics, machine learning, neural networks, optimization scheduling, management information system and decision making. So, it is possible that (AI) can impact human job nature to instead of human working behavior in the future.How can (AI) influence labor market?-How can human society job nature to be changed to artificial intelligent society? From the first intelligent perspective reason view point, artificial intelligence is making machines " intelligent" acting as humans expect people to act. Artificial intelligence has ability to distinguish computer responses from human responses, it owns knowledge to solve expert problem. From another research perspective reason view point, artificial intelligence is the study of how to make computers do things which, at the moment, people do better ( Rich & Knight, 1991, p.3).(AI) researchers are native in a variety of domains, e.g. formal tasks ( mathematics, games), tasks ( perception, robotics, natural language, common sense reasoning), expert tasks ( financial analysis, medical diagnostics, engineering, scientific analysis and other areas). From the second business perspective reason view point, (AI) is a set of many powerful tools, and methodologies for using those tools to solve business problems. From a programming perspective reason view point, (AI) includes the study of symbolic programming problem solving and search . From the third human technological perspective reason view point, today's computer can do many well-defined tasks, for example, arithmetic operations, are much faster and more accurate than human beings. However, the computers' interaction with their environment is not very sophisticated yet. How can human test whether a computer has reached the general intelligence level of a human being?
Book Synopsis What To Expect When You're Expecting Robots by : Laura Major
Download or read book What To Expect When You're Expecting Robots written by Laura Major and published by Basic Books. This book was released on 2020-10-13 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: The next generation of robots will be truly social, but can we make sure that they play well in the sandbox? Most robots are just tools. They do limited sets of tasks subject to constant human control. But a new type of robot is coming. These machines will operate on their own in busy, unpredictable public spaces. They'll ferry deliveries, manage emergency rooms, even grocery shop. Such systems could be truly collaborative, accomplishing tasks we don't do well without our having to stop and direct them. This makes them social entities, so, as robot designers Laura Major and Julie Shah argue, whether they make our lives better or worse is a matter of whether they know how to behave. What to Expect When You're Expecting Robots offers a vision for how robots can survive in the real world and how they will change our relationship to technology. From teaching them manners, to robot-proofing public spaces, to planning for their mistakes, this book answers every question you didn't know you needed to ask about the robots on the way.
Book Synopsis Robot Learning from Human Demonstration by : Sonia Dechter
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.
Book Synopsis Imitation and Social Learning in Robots, Humans and Animals by : Chrystopher L. Nehaniv
Download or read book Imitation and Social Learning in Robots, Humans and Animals written by Chrystopher L. Nehaniv and published by Cambridge University Press. This book was released on 2007-03-29 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mechanisms of imitation and social matching play a fundamental role in development, communication, interaction, learning and culture. Their investigation in different agents (animals, humans and robots) has significantly influenced our understanding of the nature and origins of social intelligence. Whilst such issues have traditionally been studied in areas such as psychology, biology and ethnology, it has become increasingly recognised that a 'constructive approach' towards imitation and social learning via the synthesis of artificial agents can provide important insights into mechanisms and create artefacts that can be instructed and taught by imitation, demonstration, and social interaction rather than by explicit programming. This book studies increasingly sophisticated models and mechanisms of social matching behaviour and marks an important step towards the development of an interdisciplinary research field, consolidating and providing a valuable reference for the increasing number of researchers in the field of imitation and social learning in robots, humans and animals.
Book Synopsis Artificial Intelligence Brings Social Economic by : Johnny Ch LOK
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?
Book Synopsis Cognitive Computing for Human-Robot Interaction by : Mamta Mittal
Download or read book Cognitive Computing for Human-Robot Interaction written by Mamta Mittal and published by Academic Press. This book was released on 2021-08-13 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human–robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: Introduces several new contributions to the representation and management of humans in autonomous robotic systems; Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; Engages with the potential repercussions of cognitive computing and HRI in the real world. Introduces several new contributions to the representation and management of humans in an autonomous robotic system Explores cognitive computing, robots and HRI, presenting a more in-depth understanding to make robots better for society Gives a challenging approach to those several repercussions of cognitive computing and HRI in the actual global scenario
Book Synopsis Human-Robot Body Experience by : Philipp Beckerle
Download or read book Human-Robot Body Experience written by Philipp Beckerle and published by Springer Nature. This book was released on 2021-06-01 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents innovative research regarding the body experience of human individuals who are using assistive robotic devices such as wearable robots or teleoperation systems. The focus is set on human-in-the-loop experiments that help to empirically evaluate how users experience devices. Moreover, these experiments allow for further examination of the underlying mechanisms of body experience through extending existing psychological paradigms, e.g., by disentangling tactile feedback from contacts. Besides reporting and discussing psychological examinations, the influence of various aspects of engineering design is investigated, e.g., different implementations of haptic interfaces or robot control. As haptics are of paramount importance in this tight type of human-robot interaction, it is explored with respect to modality as well as temporal and spatial effects. The first part of the book motivates the research topic and gives an in-depth analysis of the experimental requirements. The second and third part present experimental designs and studies of human-robot body experience regarding the upper and lower limbs as well as cognitive models to predict them. The fourth part discusses a multitude of design considerations and provides directions to guide future research on bidirectional human-machine interfaces and non-functional haptic feedback.
Book Synopsis How Artificial Intelligence Influences Future Human Job Market Change by : Johnny Ch Lok
Download or read book How Artificial Intelligence Influences Future Human Job Market Change written by Johnny Ch Lok and published by . This book was released on 2021-04-10 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can (AI) influence labor market?⦁How can human society job nature to be changed to artificial intelligent society? From the first intelligent perspective reason view point, artificial intelligence is making machines " intelligent" acting as humans expect people to act. Artificial intelligence has ability to distinguish computer responses from human responses, it owns knowledge to solve expert problem. From another research perspective reason view point, artificial intelligence is the study of how to make computers do things which, at the moment, people do better ( Rich & Knight, 1991, p.3).(AI) researchers are native in a variety of domains, e.g. formal tasks ( mathematics, games), tasks ( perception, robotics, natural language, common sense reasoning), expert tasks ( financial analysis, medical diagnostics, engineering, scientific analysis and other areas). From the second business perspective reason view point, (AI) is a set of many powerful tools, and methodologies for using those tools to solve business problems. From a programming perspective reason view point, (AI) includes the study of symbolic programming problem solving and search . From the third human technological perspective reason view point, today's computer can do many well-defined tasks, for example, arithmetic operations, are much faster and more accurate than human beings. However, the computers' interaction with their environment is not very sophisticated yet. How can human test whether a computer has reached the general intelligence level of a human being? Can a computer convince a human interrogator that it is a human? But before thinking of such advanced kinds of machines, human will start developing our own extremely simple " intelligent" machines. So, it is possible that human society job nature will to be changed to artificial intelligent society when (AI) technology is developed to the mature stage in the future.⦁Why does human need artificial intelligence machines?One of major division in (AI) is between humans who think (AI) is the only serious way of finding out how we ( human) work and human who want companies to do very smart things, independently of how we ( human) work. This is the important distinction between cognitive scientists vs engineers. One of another major division in (AI) is between symbolic (AI), which represents information through symbols and their relationships. Specific Algorithms are used to process these symbols to solve problems or deduce new knowledge and connectionist. So ( AI), which represents information in network. Biological processes underlying learning, task performance and problem solving are imitated from human mind behaviors. Thus, it is possible that artificial intelligence machines can do the better judgicious behavior to compare human.⦁How does artificial intelligence influence future working changing in automation employment and productivity aspects?In the automation changing influence aspect, as companies increasingly use robots on production lines or algorithms to optimize their logistics manage inventory, any carry out other core business functions. Technological advances are creating a new automation age in which ever-smarter and more flexible machines will be deployed on an ever larger scale in the marketplace. However, researching artificial intelligence with how influences human working nature. We need to answer these questions: How will automation transform the workplace? What will the implications for employment? And what is likely to be its impact both on productivity in the global economy and on employment?
Book Synopsis Sociable Robots and the Future of Social Relations by : J. Seibt
Download or read book Sociable Robots and the Future of Social Relations written by J. Seibt and published by IOS Press. This book was released on 2014-12-18 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: The robotics industry is growing rapidly, and to a large extent the development of this market sector is due to the area of social robotics – the production of robots that are designed to enter the space of human social interaction, both physically and semantically. Since social robots present a new type of social agent, they have been aptly classified as a disruptive technology, i.e. the sort of technology which affects the core of our current social practices and might lead to profound cultural and social change. Due to its disruptive and innovative potential, social robotics raises not only questions about utility, ethics, and legal aspects, but calls for “robo-philosophy” – the comprehensive philosophical reflection from the perspectives of all philosophical disciplines. This book presents the proceedings of the first conference in this new area, “Robo-Philosophy 2014 – Sociable Robots and the Future of Social Relations, held in Aarhus, Denmark, in August 2014. The short papers and abstracts collected here address questions of social robotics from the perspectives of philosophy of mind, social ontology, ethics, meta-ethics, political philosophy, aesthetics, intercultural philosophy, and metaphilosophy. Social robotics is still in its early stages, but it is precisely now that we need to reflect its possible cultural repercussions. This book is accessible to a wide readership and will be of interest to everyone involved in the development and use of social robotics applications, from social roboticists to policy makers.
Book Synopsis Learning to Adapt for Intelligent Robot Behavior by : Mengxi Li
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.
Book Synopsis Artificial Intelligence Future Teaching And Writing Development by : Johnny Ch LOK
Download or read book Artificial Intelligence Future Teaching And Writing Development written by Johnny Ch LOK and published by Independently Published. This book was released on 2020-05-28 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Psychological research (AI) educational social robots and students relationshipWhether can (AI) educational robots build good social relationship to students? Some scientists had attempted to do experiments to prove whether (AI) educational robots can do good or bad social relationship to students. For example, Knox, W.B. el. (2012) had ever attempted to do two experiments to research whether (AI) robot educational robot can build better or worse social relationship to compare human robot. Their two experiments aim to ask how differing conditions affect a human teacher's feedback frequency and the computational agent's learned performance. The first experiment considers the impact of a self-perceived teaching role in contrast to believing one is critiquing record. The second considers whether a human trainer will give more frequent feedback if the agent acts less ( i.e. choosing actions believed to be worse). When the trainer's recent feedback frequency decreases. From the results of those experiments, they draw three main conclusions that inform the design of agents. More broadly, these two studies indicate as early examples of a nascent technique of using agents as highly specifiable social entities in experiments on human behavior. Thus, it implies (AI) educational robots have ability to learn human teacher to teach students in good social relationship learning environment with students. Even, (AI) educational robots can build better learning relationship to compare human teachers between students, it seems (AI) robots have attractive ability t raise student individual learning interest, after which can applied to assist teachers to teach whose students in classrooms or lecture halls or online classroom channels.Other scientist had ever attempted to do experiments about " reinforcement learning" (RL) to research how result of interactive supervisory input between human teacher and both robot and software agents relationship. M. Mataric (1997) attempted to do one experiment concerns that reinforcement learning is designed for interactive supervisory input from a human teacher, several works in both robot and software agents have adapted it for human input by letting a human trainer control the reward signal. He aimed to examine the assumption, namely that the human-given reward is compatible with the traditionanl RL reward signal. He described an experimental platform with a simulated RL robot and present an analysis of real time human teaching behavior found in a study in which untrained subjects taught the robot to perform a new task. For the experiment, who reported three main observations on how people administer feedback when teaching a robot a task through reinforcement learning : (a) they use the reward channel not only for feedback, but also for future directed guidance, (b) they have a positive bias to their feedback, possibly using the signal as a motivational channel, and (c) they change their behavior as they develop a mental model of the robotic learner.
