检索结果-内蒙古大学图书馆

Role of artificial intelligence and robotics to foster the touchless travel during a pandemic: a review and research agenda

引用

INTERNATIONAL JOURNAL OF CONTEMPORARY HOSPITALITY MANAGEMENT 2021年第11期33卷 4079-4098页

作者： Gaur, Loveleen Afaq, Anam Singh, Gurmeet Dwivedi, Yogesh Kumar Amity Univ Amity Int Business Sch Naida India Univ South Pacific Sch Business & Management Suva Fiji Swansea Univ Sch Management Swansea W Glam Wales

Purpose The hospitality industry experienced an unanticipated challenge from the COVID-19 pandemic. However, research in this area is scarce. Accordingly, this study aims to unfold a three-angled research agenda to intensify the knowledge advancement in the hospitality sector. It proposes a theoretical framework by extending the protection motivation theory (PMT) to explain the guest's intent to adopt artificial intelligence (AI) and robotics as a protective measure in reaction to COVID-19. Design/methodology/approach The research is centered on outlining the pertinent literature on hospitality management practices and the guest's transformed behavior during the current crisis. This study intends to identify a research agenda based on investigating hospitality service trends in today's changing times. Findings The study sets out a research agenda that includes three dimensions as follows: AI and robotics, cleanliness and sanitation and health care and wellness. This study's findings suggest that AI and robotics may bring out definite research directions at the connection of health crisis and hospitality management, taking into account the COVID-19 crisis. Practical implications The suggested research areas are anticipated to propel the knowledge base and help the hospitality industry retrieve the COVID-19 crisis through digital transformation. AI and robotics are at the cusp of invaluable advancement that can revive the hotels while re-establish guests' confidence in safe hotel practices. The proposed research areas are likely to impart pragmatic lessons to the hospitality industry to fight against disruptive situations. Originality/value This study stands out to be pioneer research that incorporated AI and robotics to expand the PMT and highlights how behavioral choices during emergencies can bring technological revolution.

关键词： Hospitality artificial intelligence and robotics COVID-19 pandemic Cleanliness and sanitation Health care and wellness

来源：评论

学校读者我要写书评

暂无评论

ROBOCUP@HOME: Analysis and results of evolving competitions for domestic and service robots

引用

artificial intelligence 2015年 229卷 258-281页

作者： Iocchi, Luca Holz, Dirk Ruiz-del-Solar, Javier Sugiura, Komei van der Zant, Tijn Univ Roma La Sapienza Dept Comp Control & Management Engn Rome Italy Univ Bonn Autonomous Intelligent Syst Grp Bonn Germany Univ Chile Dept Elect Engn Santiago Chile Univ Chile Adv Min Technol Ctr Santiago Chile Natl Inst Informat & Commun Technol Informat Serv Platform Lab Tokyo Japan Univ Groningen Cognit Robot Lab NL-9700 AB Groningen Netherlands

Scientific competitions are becoming more common in many research areas of artificial intelligence and robotics, since they provide a shared testbed for comparing different solutions and enable the exchange of research results: Moreover, they are interesting for general audiences and industries. Currently, many major research areas in artificial intelligence and robotics are organizing multiple-year competitions that are typically associated with scientific conferences. One important aspect of such competitions is that they are organized for many years. This introduces a temporal evolution that is interesting to analyze. However, the problem of evaluating a competition over many years remains unaddressed. We believe that this issue is critical to properly fuel changes over the years and measure the results of these decisions. Therefore, this article focuses on the analysis and the results of evolving competitions. In this article, we present the ROBOCUP@HOME competition, which is the largest worldwide competition for domestic service robots, and evaluate its progress over the past seven years. We show how the definition of a proper scoring system allows for desired functionalities to be related to tasks and how the resulting analysis fuels subsequent changes to achieve general and robust solutions implemented by the teams. Our results show not only the steadily increasing complexity of the tasks that ROBOCUP@HOME robots can solve but also the increased performance for all of the functionalities addressed in the competition. We believe that the methodology used in ROBOCUP@HOME for evaluating competition advances and for stimulating changes can be applied and extended to other robotic competitions as well as to multi-year research projects involving artificial intelligence and robotics. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Robotic competitions artificial intelligence and robotics Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Effects of COVID-19 on hotel marketing and management: a perspective article

引用

INTERNATIONAL JOURNAL OF CONTEMPORARY HOSPITALITY MANAGEMENT 2020年第8期32卷 2563-2573页

作者： Jiang, Yangyang Wen, Jun Univ Nottingham Ningbo China Nottingham Univ Business Sch China Ningbo Peoples R China Edith Cowan Univ Sch Business & Law Joondalup Australia

Purpose This paper aims to discuss the effects of COVID-19 on hotel marketing and management practices and outlines a three-pronged research agenda to stimulate knowledge development in the hotel sector. Design/methodology/approach This paper is based on an overview of the relevant literature on hotel marketing and management and the hotel guest behavior. The authors also investigated hospitality service trends to propose a research agenda. Findings This paper presents a research agenda from three dimensions - artificial intelligence (AI) and robotics, hygiene and cleanliness and health and health care. First, different types of AI (mechanical, thinking and feeling) might open up distinct research streams at the intersection of health crises and hotel management, in light of the COVID-19 pandemic. Additionally, this paper recommends that researchers move beyond typical perspectives on the antecedents and outcomes of hotel hygiene and cleanliness to delve into guests' perceptions of the cleanliness of specific hotel surfaces. Furthermore, a more in-depth analysis is warranted about the evolving relationship between hotels and the health-care sector. Practical implications The recommended research areas are intended to advance the knowledge base to help hotels recover from the COVID-19 pandemic. The suggested research streams are expected to provide actionable insights to promote the development and sustainability of the hotel sector. Originality/value This paper appears to be a frontier study, critically examining possible effects of the COVID-19 pandemic on hotel marketing and management practices and how hoteliers may respond to such challenges to recover after this pandemic.

关键词： artificial intelligence and robotics Hygiene and cleanliness Health and health care Hotel management COVID-19 pandemic

来源：评论

学校读者我要写书评

暂无评论

Mapping the service recovery research landscape: A bibliometric-based systematic review

引用

PSYCHOLOGY & MARKETING 2023年第10期40卷 2060-2087页

作者： Mir, Mahmood Ashraf, Rohail Syed, Tahir Abbas Ali, Sara Nawaz, Raheel Manchester Metropolitan Univ Dept Operat Technol Events & Hospitality Managemen Manchester England Manchester Metropolitan Univ Dept Mkt Retail & Tourism Manchester England Univ Manchester Dept Management Sci & Mkt Manchester England Natl Univ Sci & Technol NUST Dept Robot & Artificial Intelligence Islamabad Pakistan Staffordshire Univ Pro Vice Chancellor Dept Digital Transformat Stoke On Trent Staffs England

With businesses under increasing pressure to provide excellent customer service, postfailure recovery strategies have become critical for long-term customer satisfaction and loyalty. The domain of service recovery has extensively been examined in academia;however, systematic studies that provide a consolidated overview remains scant. To this end, we provide a systematic review and synthesis of service recovery literature by conducting a bibliometric-based cocitation analysis of 24,741 cited references from 1020 articles from across disciplines. The study identifies 10 major research clusters that represent different research streams of service recovery and explores their intellectual foundations. In addition, the research presents a conceptual framework to serve as a parsimonious guide for both practitioners and researchers. Furthermore, the study reveals a number of gaps in the existing literature and suggests promising directions for further investigation, including but not limited to: expanding methodological horizons in service recovery research, understanding service recovery mechanisms in Metaverse and synthetic environments, globalizing service recovery research, revitalizing service recovery processes in the age of artificial intelligence and robotics, investigating service recovery as an investment, and exploring service recovery in shared economies. Notably, this study serves managers, firstly, by providing them with a parsimonious structure of service recovery field that could help identify areas of improvement in their own service recovery systems and, secondly, by highlighting areas where academic knowledge base could inform industry solutions.

关键词： artificial intelligence and robotics bibliometrics metaverse service failure service recovery sharing economy systematic review

来源：评论

学校读者我要写书评

暂无评论

COMPACT REPRESENTATIONS OF UNCERTAINTY IN CLUSTERING

COMPACT REPRESENTATIONS OF UNCERTAINTY IN CLUSTERING

引用

作者： Craig Stuart Greenberg University of Massachusetts Amherst

学位级别：博士

Flat clustering and hierarchical clustering are two fundamental tasks, often used to discover meaningful structures in data, such as subtypes of cancer, phylogenetic relationships, taxonomies of concepts, and cascades of particle decays in particle physics. When multiple clusterings of the data are possible, it is useful to represent uncertainty in clustering through various probabilistic quantities, such as the distribution over partitions or tree structures, and the marginal probabilities of subpartitions or subtrees. Many compact representations exist for structured prediction problems, enabling the efficient computation of probability distributions, e.g., a trellis structure and corresponding Forward-Backward algorithm for Markov models that model sequences. However, no such representation has been proposed for either flat or hierarchical clustering models. In this thesis, we present our work developing data structures and algorithms for computing probability distributions over flat and hierarchical clusterings, as well as for finding maximum a posteriori (MAP) flat and hierarchical clusterings, and various marginal probabilities, as given by a wide range of energy-based clustering models. First, we describe a trellis structure that compactly represents distributions over flat or hierarchical clusterings. We also describe related data structures that represent approximate distributions. We then present algorithms that, using these structures, allow us to compute the partition function, MAP clustering, and the marginal proba- bilities of a cluster (and sub-hierarchy, in the case of hierarchical clustering) exactly. We also show how these and related algorithms can be used to approximate these values, and analyze the time and space complexity of our proposed methods. We demonstrate the utility of our approaches using various synthetic data of interest as well as in two real world applications, namely particle physics at the Large Hadron Collider at CERN and in can

关键词： artificial intelligence and robotics Discrete Mathematics and Combinatorics Theory and Algorithms

来源：评论

学校读者我要写书评

暂无评论

Reasoning About User Feedback Under Identity Uncertainty in Knowledge Base Construction

Reasoning About User Feedback Under Identity Uncertainty in ...

引用

作者： Ariel Kobren University of Massachusetts Amherst

学位级别：博士

Intelligent, automated systems that are intertwined with everyday life---such as Google Search and virtual assistants like Amazon’s Alexa or Apple’s Siri---are often powered in part by knowledge bases (KBs), i.e., structured data repositories of entities, their attributes, and the relationships among them. Despite a wealth of research focused on automated KB construction methods, KBs are inevitably imperfect, with errors stemming from various points in the construction pipeline. Making matters more challenging, new data is created daily and must be integrated with existing KBs so that they remain up-to-date. As the primary consumers of KBs, human users have tremendous potential to aid in KB construction by contributing feedback that identifies spurious and missing entity attributes and relations. However, correctly integrating user feedback with an existing KB is complicated by the necessity to resolve , i.e., uncertainty regarding to which real-world entity a piece of data refers. Identity uncertainty abounds in the collection of raw evidence from which a KB is built. Moreover, it also gives rise to identity uncertainty , when KB entities, which were affected by user feedback, are split or merged. In this dissertation, we present a continuous reasoning framework capable of integrating user feedback with a KB, under identity certainty. To begin, we introduce Grinch, an online entity resolution (ER) algorithm---with provable correctness guarantees---capable of merging and splitting KB entities as new data arrives. We show that Grinch is efficient and achieves state-of-the-art performance in ER as well as in clustering. Next, we propose a method for using Grinch to resolve identity uncertainty in a KB's underlying data as well as in user feedback. Our approach is based on representing user feedback as , i.e., first class KB objects that participate in all parts of KB construction. Furthermore, we introduce a structured representation for feedback comprised of and

关键词： artificial intelligence and robotics

来源：评论

学校读者我要写书评

暂无评论

PROBABILISTIC MODELS FOR IDENTIFYING AND EXPLAINING CONTROVERSY

PROBABILISTIC MODELS FOR IDENTIFYING AND EXPLAINING CONTROVE...

引用

作者： MYUNGHA JANG University of Massachusetts Amherst

学位级别：博士

Navigating controversial topics on the Web encourages social awareness, supports civil discourse, and promotes critical literacy. While search of controversial topics par- ticularly requires users to use their critical literacy skills on the content, educating people to be more critical readers is known to be a complex and long-term process. Therefore, we are in need of search engines that are equipped with techniques to help users to understand controversial topics by identifying them and explaining why they are controversial. A few approaches for identifying controversy have worked reason- ably well in practice, but they are narrow in scope and exhibit limited performance. In this thesis, we first focus on understanding the theoretical grounding of the state-of-the-art algorithm. We derive an underlying probabilistic model that explains the state-of-the-art controversy detection algorithm. We revisit the properties and as- sumptions from the derived model, and propose new methods to identify controversy on Webpages. We then point out that the current approaches for controversy detec- tion do not consider time while controversy is a dynamically changing phenomenon. This causes current methods to have delays in recognizing emerging controversial topics or exaggerated effects on outdated controversies. We address time-adaptable controversy detection by estimating the dynamically-changing controversy trend of topic by interpolating the observed level of contention and the public interest over time on the topic. Finally, we offer a method that explains controversy by generating a summary of each stance. Our method ranks social media postings using a score of how likely it is that the given post can be a representative summary of controversy.

关键词： artificial intelligence and robotics Computer Sciences Databases and Information Systems Social Influence and Political Communication Social Media

来源：评论

学校读者我要写书评

暂无评论

FROM OPTIMIZATION TO EQUILIBRATION: UNDERSTANDING AN EMERGING PARADIGM IN artificial intelligence AND MACHINE LEARNING

FROM OPTIMIZATION TO EQUILIBRATION: UNDERSTANDING AN EMERGIN...

引用

作者： IAN GEMP University of Massachusetts Amherst

学位级别：博士

Many existing machine learning (ML) algorithms cannot be viewed as gradient descent on some single objective. The solution trajectories taken by these algorithms naturally exhibit rotation, sometimes forming cycles, a behavior that is not expected with (full-batch) gradient descent. However, these algorithms can be viewed more generally as solving for the equilibrium of a game with possibly multiple competing objectives. Moreover, some recent ML models, specifically generative adversarial net- works (GANs) and its variants, are now explicitly formulated as equilibrium problems. Equilibrium problems present challenges beyond those encountered in optimization such as limit-cycles and chaotic attractors and are able to abstract away some of the difficulties encountered when training models like GANs. In this thesis, I aim to advance our understanding of equilibrium problems so as to improve state-of-the-art in GANs and related domains. In the following chapters, I will present work on 1. designing a no-regret framework for solving monotone equilibrium problems in online or streaming settings (with applications to Reinforcement Learning), 2. ensuring convergence when training a GAN to fit a normal distribution to data by Crossing-the-Curl, 3. improving state-of-the-art image generation with techniques derived from the- ory, 4. and borrowing tools from dynamical systems theory for analyzing the complex dynamics of GAN training.

关键词： artificial intelligence and robotics Dynamical Systems

来源：评论

学校读者我要写书评

暂无评论

The Use of Cultural Algorithms to Learn the Impact of Climate on Local Fishing Behavior in Cerro Azul, Peru

The Use of Cultural Algorithms to Learn the Impact of Climat...

引用

作者： Kattan, Khalid Wayne State University

学位级别：Ph.D.

Recently it has been found that the earth’s oceans are warming at a pace that is 40% faster than predicted by a United Nations panel a few years ago. As a result, 2019 has become the warmest year on record for the earth’s oceans. That is because the oceans have acted as a buffer by absorbing 93% of the heat produced by the greenhouse gases [40]. The impact of the oceanic warming has already been felt in terms of the periodic warming of the Pacific Ocean as an effect of the ENSO process. The ENSO process is a cycle of warming and subsequent cooling of the Pacific Ocean that can last over a period of years. This cycle was first documented by Peruvian fishermen in the early 1600’s. So it has been part of the environmental challenges that have been presented to economic agents throughout the world since then. It has even been suggested that the cycle has increased in frequency over the years, perhaps in response to the overall issues related to global warming. Although the onset of the ENSO cycle might be viewed as disruption of the fishing economy in a given area, there is some possibility that over time agents have been able to develop strategic responses to these changes to as to reduce the economic risk associated with them. During that time the Cerro Azul, Peru was in the process of emerging from one of the largest ENSOs on record. This was perceived to be a great opportunity to see how the collective bodies of fishermen were able to alter their fishing strategies to deal with these more uncertain times. Our results suggest that indeed the collective economic response of the fishermen demonstrates an ability to respond to the unpredictabilities of climate change, but at a cost. It is clear that the fishermen have gained the collective knowledge over the years to produce a coordinated response that can be observed at a higher level. Of course, this knowledge can be used to coordinate activities only if it is communicated socially within the society. Although our dat

关键词： Climate Change Cultural Algorithms Evolutionary Algorithms Machine Learning Multi-Objective Optimization Nonlinear Regression artificial intelligence and robotics Computer Sciences History of Art, Architecture, and Archaeology

来源：评论

学校读者我要写书评

暂无评论

Integration of Robotic Perception, Action, and Memory

Integration of Robotic Perception, Action, and Memory

引用

作者： Li Yang Ku University of Massachusetts Amherst

学位级别：博士

In the book "On intelligence", Hawkins states that intelligence should be measured by the capacity to memorize and predict patterns. I further suggest that the ability to predict action consequences based on perception and memory is essential for robots to demonstrate intelligent behaviors in unstructured environments. However, traditional approaches generally represent action and perception separately---as computer vision modules that recognize objects and as planners that execute actions based on labels and poses. I propose here a more integrated approach where action and perception are combined in a memory model, in which a sequence of actions can be planned based on predicted action outcomes. In this framework, hierarchical visual features based on convolutional neural networks are introduced to capture the essential affordances. These features in different hierarchies are associated with robot controllers of corresponding kinematic subchains to support manipulation. Through learning from demonstration, both actions and informative features in the memory model can be learned efficiently. As more demonstrations are recorded and more interactions are observed, the robot becomes more capable of predicting the consequences of actions, thus, is better at planning sequences of actions to solve tasks under different circumstances.

关键词： artificial intelligence and robotics Cognitive Neuroscience robotics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：