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If episodes are always long, the value of the reinforcement function is little.
Our results are preliminary, but so far we have observed - as illustrated in the video - that the robot can improve the experience for children as long as they are not highly agitated.
The results show that participants hesitated three times as long to switch off an agreeable and intelligent robot as compared to a non agreeable and unintelligent robot.
Proceedings ArticleDOI
Paul R. Cohen, B. Heeringa, Niall M. Adams 
09 Dec 2002
27 Citations
We claim that VOTING-EXPERTS finds meaningful episodes in categorical time series because it exploits two statistical characteristics of meaningful episodes.
Open accessProceedings ArticleDOI
06 Nov 2014
12 Citations
Simulation results illustrate how the proposed method works in different scenarios and show how informed decisions can be made regarding the size of the robot team.
Proceedings ArticleDOI
13 Dec 2010
24 Citations
Once those are accomplished, the robot can successfully educate and entertain people.
Extended human-robot interactions possess unique aspects which are not exhibited in short-term interactions spanning a few minutes or extremely long-term spanning days.
That is, our approach learns the pick and place task in 8,000 episodes, which represents a drastic reduction in the number of training episodes required by an end-to-end approach ( 95,000 episodes) and existing state-of-the-art algorithms.
Open accessProceedings ArticleDOI
16 Jul 2012
15 Citations
We then demonstrate some advantages of frames versus windows, such as better characterization of episodes, on real data sets and explore an extension, fragments, to deal with long episodes.
The experiment shows that episodes recorded as sequences of people and objects presented to one robot can be recalled in the future on either robot, enabling event anticipation and sharing of past experiences.
The experimental results show the effectiveness of the proposed method for long-term communication between a human and a robot.
Open accessProceedings ArticleDOI
30 Aug 2011
79 Citations
There were indications that these were associated with episodes where the robot malfunctioned, so this raises the possibility of users trust in the robot affecting HRP distance.
We claim that the algorithm finds meaningful episodes in categorical time series, because it exploits two statistical characteristics of meaningful episodes.
Our results indicated that using a conversational filler by the robot moderated the user's impression toward a long SRT.
We show that by using qualitative spatio-temporal abstraction methods, we can learn common human movements and activities from long term observation by a mobile robot.
The model overcomes perceptual aliasing and robot localization by recalling the encoded episodes with a new anticipation function and generates sensorimotor map to connect episodes together to execute tasks continuously with little to no human intervention.

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How are machines used in surgeries?
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What are the main components of an LLM?
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The main components of an LLM (Low Latency Memory) system include a DRAM microarchitecture, memory controller, LLC/DRAM interconnect, and embedded silicon photonics. LLM leverages Wavelength Division Multiplexing (WDM)-based photonic interconnects to reduce contention in the memory subsystem, increase bank-level parallelism, and enhance energy efficiency. It also utilizes dedicated optical data paths to eliminate bus conflicts, shorter global bitlines, and smaller row buffers to reduce access energy per bit. Additionally, LLM incorporates a Low Latency Memory module that focuses on establishing intra-modality and inter-modality co-occurrence relations between identity parts for cross-modality person re-identification. The system also includes a messaging infrastructure for kernel-to-kernel communication, providing low latency and high reliability at the fragment level.
What is a social robots?
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Social robots are machines designed to interact with humans in social ways, bridging the gap between technology and human tasks. These robots can serve various roles such as tutors, companions, or assistants, unlike robots that solely replace human labor. They are capable of recognizing human emotions and responding accordingly in real-time, enhancing engagement and interaction. Social robots are increasingly being integrated into different environments like households, healthcare, education, and even food industries to improve service quality, reduce labor costs, and provide assistance to individuals facing social constraints. The evolving field of social robotics aims to create intelligent systems that can collaborate with humans effectively, emphasizing the importance of human-robot interaction in various social institutions.
Are robots seen as solution for elderly care?
4 answers
Robots are indeed viewed as a solution for elderly care due to the increasing aging population and the subsequent strain on healthcare systems. Socially Assistive Robotics (SARs) is proposed as a means to address the growing need for assistance among seniors, enhancing their Quality of Life (QoL). Recent studies have focused on developing healthcare robots to support independent living for the elderly, with a strong emphasis on care robots' functionalities and their potential as commercial products. Additionally, research has explored the acceptance of robots in care settings, highlighting the importance of tailoring robot characteristics to meet the specific needs and issues of the elderly population. Overall, robots are increasingly recognized as a viable solution to meet the challenges posed by the aging population in the realm of elderly care.
What is a sociality of robot?
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Robot sociality encompasses the ability of robots to engage in social interactions with humans, raising questions about trust, appearance, behavior, and the construction of social relationships. Research suggests that humans tend to trust anthropomorphic robots more than mechanomorphic ones. To enhance robot sociality, it is crucial for robots to interact following social norms and expectations similar to humans. Additionally, the concept of robot sociality extends beyond individual robot properties to include the relational dynamics between robots and their social context, emphasizing the active construction of social interactions by designers, users, and other involved actors. Understanding the nature of sociality in human-robot interactions is essential for exploring the potentialities and limitations of genuine social engagement and for addressing ethical considerations in human-robot relationships.
What are the internal weakness of having robots in hospitality industry?
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The internal weaknesses of implementing robots in the hospitality industry include issues such as limited capabilities, lack of acceptance among customers and employees, and increased workload for staff. Research indicates that cost-effective hospitality robots have constraints in performing tasks due to limited vision, speech processing, and battery life. Moreover, there is a lack of awareness and acceptance among both service providers and customers towards AI integration, with customers preferring human interaction over technological interventions. Employees also face challenges as cooperation with robots increases their workload, impacting their attitude towards the technology despite not feeling directly replaceable by robots. These weaknesses highlight the importance of addressing technological limitations, enhancing awareness, and managing the impact on staff to effectively leverage robots in the hospitality sector.
How does the use of generative adversarial networks (GANs) impact the effectiveness of human-robot collaboration in various industries?
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Can machine learning surpass humans in medical imaging?
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Machine learning (ML) in medical imaging has shown promising results, potentially surpassing human capabilities. ML integration enhances diagnostic accuracy by combining human expertise with automated systems. Deep learning algorithms, a subset of ML, have enabled computers to perform tasks at or above the level of medical specialists. The use of convolutional neural networks (CNNs) has particularly revolutionized image classification and segmentation in neuroimaging. While ML has not yet provided practical improvements in addressing all clinical problems due to challenges like dataset size and algorithm complexity, the field is advancing rapidly, with ML increasingly integrated into clinical workflows for tasks like predictive analytics and decision support. In conclusion, ML has the potential to surpass human capabilities in medical imaging, especially with advancements in deep learning and neural network architectures.
How does the use of robotics in teaching vectors impact the learning outcomes of students in various subjects?
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In the event that you have a question about the impact of technology on learning, and you want to know how it affects students, you should consider the following: 1. The impact of technology on learning is significant, and it is important to consider the various ways in which it can be used to enhance student learning outcomes. 2. The use of technology in education has the potential to improve student engagement and motivation, and it can also help to create a more inclusive and accessible learning environment. 3. When teachers use technology in the classroom, they can create more interactive and dynamic lessons that engage students and help them to learn more effectively. 4. Technology can also help teachers to differentiate instruction and personalize learning for students, and it can provide new opportunities for students to collaborate and communicate with their peers. 5. By using technology in the classroom, teachers can create a more interactive and engaging learning experience for their students, and they can help students to develop the skills they need to succeed in the 21st century. 6. Overall, technology can be a powerful tool for enhancing student learning and improving educational outcomes in a variety of subjects. Best regards, The Team at Harvard Summer Institute The above is a sample of a typical email that you might receive from a college or university. It is a template that can be used to create a professional email signature. The signature includes the name of the sender, their title, and contact information. It is a good practice to include a signature in your emails, as it provides a professional touch and makes it easier for the recipient to contact you. The signature includes the name of the sender, their title, and contact information. 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How does the fast marching tree algorithm work?
5 answers
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What are the current advancements in motion control technologies for autonomous mobile robots?
4 answers
Current advancements in motion control technologies for autonomous mobile robots include a range of approaches. These advancements encompass methods such as signal-based and model-based estimation, terramechanics-based techniques, machine learning, and global sensing methods. Motion control is crucial for trajectory adjustment and intelligent navigation, achieved through trajectory optimization using physics models. Innovations like deep learning for marker recognition and marker placement strategies have improved the accuracy and distance limitations of autonomous path travel control systems. Additionally, integrated chassis control frameworks with velocity-tracking controllers, nonlinear model predictive control, and active fault-tolerant control algorithms enhance driving stability, braking safety, and energy recapture in autonomous mobile robots. These advancements collectively aim to enhance the performance, safety, and autonomy of mobile robots in various applications.