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๋ก๋ด์ ์ ์ฒด ์ธ์ด๊ฐ ์ฌํ์ ํน์ฑ๊ณผ ์ธ๊ฐ ์ ์ฌ์ฑ์ ๋ฏธ์น๋ ์ํฅ
ํ์๋
ผ๋ฌธ (์์ฌ) -- ์์ธ๋ํ๊ต ๋ํ์ : ์ฌํ๊ณผํ๋ํ ์ฌ๋ฆฌํ๊ณผ, 2021. 2. Sowon Hahn.The present study investigated the role of robotsโ body language on perceptions of social qualities and human-likeness in robots. In experiment 1, videos of a robotโs body language varying in expansiveness were used to evaluate the two aspects. In experiment 2, videos of social interactions containing the body languages in experiment 1 were used to further examine the effects of robotsโ body language on these aspects. Results suggest that a robot conveying open body language are evaluated higher on perceptions of social characteristics and human-likeness compared to a robot with closed body language. These effects were not found in videos of social interactions (experiment 2), which suggests that other features play significant roles in evaluations of a robot. Nonetheless, current research provides evidence of the importance of robotsโ body language in judgments of social characteristics and human-likeness. While measures of social qualities and human-likeness favor robots that convey open body language, post-experiment interviews revealed that participants expect robots to alleviate feelings of loneliness and empathize with them, which require more diverse body language in addition to open body language. Thus, robotic designers are encouraged to develop robots capable of expressing a wider range of motion. By enabling complex movements, more natural communications between humans and robots are possible, which allows humans to consider robots as social partners.๋ณธ ์ฐ๊ตฌ๋ ๋ก๋ด์ ์ ์ฒด ์ธ์ด๊ฐ ์ฌํ์ ํน์ฑ๊ณผ ์ธ๊ฐ๊ณผ์ ์ ์ฌ์ฑ์ ๋ํ ์ธ๊ฐ์ ์ธ์์ ๋ฏธ์น๋ ์ํฅ์ ํ์ํ์๋ค. ์คํ 1์์๋ ๋ก๋ด์ ๊ฐ๋ฐฉ์ ์ ์ฒด ์ธ์ด๊ฐ ๋ฌ์ฌ๋ ์์๊ณผ ํ์์ ์ ์ฒด ์ธ์ด๊ฐ ๋ฌ์ฌ๋ ์์์ ํตํด ์ด๋ฌํ ์ธ ๊ฐ์ง ์ธก๋ฉด์ ์ดํด๋ณด์๋ค. ์คํ 2์์๋ ์คํ 1์ ์ ์ฒด ์ธ์ด๊ฐ ํฌํจ๋ ๋ก๋ด๊ณผ ์ฌ๋ ๊ฐ์ ์ํธ์์ฉ ์์์ ํ์ฉํ์ฌ ๋ก๋ด์ ์ ์ฒด ์ธ์ด๊ฐ ์ ๋ ๊ฐ์ง ์ธก๋ฉด์ ๋ฏธ์น๋ ์ํฅ์ ํ์ํ์๋ค. ๊ฒฐ๊ณผ์ ์ผ๋ก, ์ฌ๋๋ค์ ํ์์ ์ ์ฒด ์ธ์ด๋ฅผ ํํํ๋ ๋ก๋ด์ ๋นํด ๊ฐ๋ฐฉ์ ์ ์ฒด ์ธ์ด๋ฅผ ํํํ๋ ๋ก๋ด์ ์ฌํ์ ํน์ฑ๊ณผ ์ธ๊ฐ๊ณผ์ ์ ์ฌ์ฑ์ ๋ํ ์ธ์ ๋ฉด์์ ๋ ๋๊ฒ ํ๊ฐํ๋ค๋ ๊ฒ์ ํ์ธํ์๋ค. ๊ทธ๋ฌ๋ ์ฌ๋๊ณผ์ ์ํธ์์ฉ์ ๋ด์ ์์์ ํตํด์๋ ์ด๋ฌํ ํจ๊ณผ๊ฐ ๋ฐ๊ฒฌ๋์ง ์์์ผ๋ฉฐ, ์ด๋ ์คํ 2์ ํฌํจ๋ ์์ฑ ๋ฑ์ ๋ค๋ฅธ ํน์ง์ด ๋ก๋ด์ ๋ํ ํ๊ฐ์ ์ค์ํ ์ญํ ์ ํ๋ค๋ ๊ฒ์ ์์ฌํ๋ค. ๊ทธ๋ผ์๋ ๋ถ๊ตฌํ๊ณ , ๋ณธ ์ฐ๊ตฌ๋ ๋ก๋ด์ ์ ์ฒด ์ธ์ด๊ฐ ์ฌํ์ ํน์ฑ ๋ฐ ์ธ๊ฐ๊ณผ์ ์ ์ฌ์ฑ์ ๋ํ ์ธ์์ ์ค์ํ ์์ธ์ด ๋๋ค๋ ๊ทผ๊ฑฐ๋ฅผ ์ ๊ณตํ๋ค. ์ฌํ์ ํน์ฑ๊ณผ ์ธ๊ฐ๊ณผ์ ์ ์ฌ์ฑ์ ์ฒ๋์์๋ ๊ฐ๋ฐฉ์ ์ ์ฒด ์ธ์ด๋ฅผ ํํํ๋ ๋ก๋ด์ด ๋ ๋๊ฒ ํ๊ฐ๋์์ง๋ง, ์คํ ํ ์ธํฐ๋ทฐ์์๋ ๋ก๋ด์ด ์ธ๋ก์ด ๊ฐ์ ์ ์ํํ๊ณ ๊ณต๊ฐํ๊ธฐ๋ฅผ ๊ธฐ๋ํ๋ ๊ฒ์ผ๋ก ๋ํ๋ ์ด ์ํฉ๋ค์ ์ ์ ํ ํ์์ ์ ์ฒด ์ธ์ด ๋ํ ๋ฐฐ์ ํ ์ ์๋ค๊ณ ํด์ํ ์ ์๋ค. ์ด์ ๋ฐ๋ผ ๋ณธ ์ฐ๊ตฌ์์๋ ๋ก๋ด ๋์์ด๋๋ค์ด ๋์ฑ ๋ค์ํ ๋ฒ์์ ์์ง์์ ํํํ ์ ์๋ ๋ก๋ด์ ๊ฐ๋ฐํ๋๋ก ์ฅ๋ คํ๋ค. ๊ทธ๋ ๋ค๋ฉด ์ฌ์ธํ ์์ง์์ ๋ฐ๋ฅธ ์์ฐ์ค๋ฌ์ด ์์ฌ์ํต์ ํตํด ์ธ๊ฐ์ด ๋ก๋ด์ ์ฌํ์ ๋๋ฐ์๋ก ์ธ์ํ ์ ์์ ๊ฒ์ด๋ค.Chapter 1. Introduction 1
1. Motivation 1
2. Theoretical Background and Previous Research 3
3. Purpose of Study 12
Chapter 2. Experiment 1 13
1. Objective and Hypotheses 13
2. Methods 13
3. Results 21
4. Discussion 31
Chapter 3. Experiment 2 34
1. Objective and Hypotheses 34
2. Methods 35
3. Results 38
4. Discussion 50
Chapter 4. Conclusion 52
Chapter 5. General Discussion 54
References 60
Appendix 70
๊ตญ๋ฌธ์ด๋ก 77Maste
From individual characters to large crowds: augmenting the believability of open-world games through exploring social emotion in pedestrian groups
Crowds of non-player characters improve the game-play experiences of open-world video-games. Grouping is a common phenomenon of crowds and plays an important role in crowd behaviour. Recent crowd simulation research focuses on group modelling in pedestrian crowds and game-designers have argued that the design of non-player characters should capture and exploit the relationship between characters. The concepts of social groups and inter-character relationships are not new in social psychology, and on-going work addresses the social life of emotions and its behavioural consequences on individuals and groups alike. The aim of this paper is to provide an overview of current research in social psychology, and to use the findings as a source of inspiration to design a social network of non-player characters, with application to the problem of group modelling in simulated crowds in computer games
Automatic Context-Driven Inference of Engagement in HMI: A Survey
An integral part of seamless human-human communication is engagement, the
process by which two or more participants establish, maintain, and end their
perceived connection. Therefore, to develop successful human-centered
human-machine interaction applications, automatic engagement inference is one
of the tasks required to achieve engaging interactions between humans and
machines, and to make machines attuned to their users, hence enhancing user
satisfaction and technology acceptance. Several factors contribute to
engagement state inference, which include the interaction context and
interactants' behaviours and identity. Indeed, engagement is a multi-faceted
and multi-modal construct that requires high accuracy in the analysis and
interpretation of contextual, verbal and non-verbal cues. Thus, the development
of an automated and intelligent system that accomplishes this task has been
proven to be challenging so far. This paper presents a comprehensive survey on
previous work in engagement inference for human-machine interaction, entailing
interdisciplinary definition, engagement components and factors, publicly
available datasets, ground truth assessment, and most commonly used features
and methods, serving as a guide for the development of future human-machine
interaction interfaces with reliable context-aware engagement inference
capability. An in-depth review across embodied and disembodied interaction
modes, and an emphasis on the interaction context of which engagement
perception modules are integrated sets apart the presented survey from existing
surveys
A Multi-Agent Simulation of Serious Games to Predict Their Impact on E-Learning Processes
Serious games constitute actually a recent and attractive
way supposed to replace the classical boring courses. However,
the choice of the adapted serious game to a specific learning
environment remains a challenging task that makes teachers unwilling
to adopt this concept. To fill this gap, we present, in this paper,
a multi-agent-based simulator allowing to predict the impact of a
serious game integration in a learning environment given several
game and players characteristics. As results, the presented tool
gives intensities of several emotional aspects characterizing learners
reactions to the serious game adoption. The presented simulator
is tested to predict the effect of basing a coding course on the
serious game โCodeCombatโ. The obtained results are compared with
feedbacks of using the same serious game in a real learning process
Computational model of negotiation skills in virtual artificial agents
Negotiation skills represent crucial abilities for engaging in effective social interactions in formal and informal settings. Serious games, intelligent systems and virtual agents can provide solid tools upon which one-to-one training and assessment can be reliably made available. The aim of the present work is to fill the gap between the recent growing interest towards soft skills, and the lack of a robust and modern methodology for supporting their investigation. A computational model for the development of Enact, a 3D virtual intelligent platform for training and testing negotiation skills, will be presented. The serious game allows users to interact with simulated peers in scenarios depicting daily life situations and receive a psychological assessment and adaptive training reflecting their negotiation abilities. To pursue this goal, this work has gone through different research stages, each with a unique methodology, results and discussion described in its specific section. In the first phase, the platform was designed to operationalize the examined negotiation theory, developed and assessed. The negotiation styles considered, consistently with previous findings, have been found not to correlate with personality traits, coping strategies and perceived self-efficacy. The serious game has been widely tested for its usability and underwent two development and release stages aimed at improving its accuracy, usability and likeability. The variables measured by the platform have been found to predict in all cases at least two of the negotiation styles considered. Concerning the user feedback, the game has been judged as useful, more pleasant than the traditional test, and the perceived time spent on the game resulted significantly lower than the real time spent. In the second stage of this research, the game scenarios were used to collect a dataset of documents containing natural language negotiations between users and the virtual agents. The dataset was used to assess the correlations between the personal pronouns' use and the negotiation styles. Results showed that more engaged styles generally used pronouns with a significantly higher frequency than less engaged styles. Styles with a high concern for self showed a higher frequency of singular personal pronouns while styles with a high concern for others used significantly more relational pronouns. The corpus of documents was also used to perform multiclass classification on the negotiation styles using machine learning. Both linear (SVM) and non-linear models (MNB, CNN) performed reliably with a state-of-the-art accuracy
Personality representation: predicting behaviour for personalised learning support
The need for personalised support systems comes from the growing number of students that are being supported within institutions with shrinking resources. Over the last decade the use of computers and the Internet within education has become more predominant. This opens up a range of possibilities in regard to spreading that resource further and more effectively. Previous attempts to create automated systems such as intelligent tutoring systems and learning companions have been criticised for being pedagogically ineffective and relying on large knowledge sources which restrict their domain of application. More recent work on adaptive hypermedia has resolved some of these issues but has been criticised for the lack of support scope, focusing on learning paths and alternative content presentation. The student model used within these systems is also of limited scope and often based on learning history or learning styles.This research examines the potential of using a personality theory as the basis for a personalisation mechanism within an educational support system. The automated support system is designed to utilise a personality based profile to predict student behaviour. This prediction is then used to select the most appropriate feedback from a selection of reflective hints for students performing lab based programming activities. The rationale for the use of personality is simply that this is the concept psychologists use for identifying individual differences and similarities which are expressed in everyday behaviour. Therefore the research has investigated how these characteristics can be modelled in order to provide a fundamental understanding of the student user and thus be able to provide tailored support. As personality is used to describe individuals across many situations and behaviours, the use of such at the core of a personalisation mechanism may overcome the issues of scope experienced by previous methods.This research poses the following question: can a representation of personality be used to predict behaviour within a software system, in such a way, as to be able to personalise support?Putting forward the central claim that it is feasible to capture and represent personality within a software system for the purpose of personalising services.The research uses a mixed methods approach including a number and combination of quantitative and qualitative methods for both investigation and determining the feasibility of this approach.The main contribution of the thesis has been the development of a set of profiling models from psychological theories, which account for both individual differences and group similarities, as a means of personalising services. These are then applied to the development of a prototype system which utilises a personality based profile. The evidence from the evaluation of the developed prototype system has demonstrated an ability to predict student behaviour with limited success and personalise support.The limitations of the evaluation study and implementation difficulties suggest that the approach taken in this research is not feasible. Further research and exploration is required โparticularly in the application to a subject area outside that of programming
The Effectiveness Of Virtual Humans Vs. Pre-recorded Humans In A Standardized Patient Performance Assessment
A Standardized Patient (SP) is a trained actor who portrays a particular illness to provide training to medical students and professionals. SPs primarily use written scripts and additional paper-based training for preparation of practical and board exams. Many institutions use various methods for training such as hiring preceptors for reenactment of scenarios, viewing archived videos, and computer based training. Currently, the training that is available can be enhanced to improve the level of quality of standardized patients. The following research is examining current processes in standardized patient training and investigating new methods for clinical skills education in SPs. The modality that is selected for training can possibly affect the performance of the actual SP case. This paper explains the results of a study that investigates if there is a difference in the results of an SP performance assessment. This difference can be seen when comparing a virtual human modality to that of a pre-recorded human modality for standardized patient training. The sample population navigates through an interactive computer based training module which provides informational content on what the roles of an SP are, training objectives, a practice session, and an interactive performance assessment with a simulated Virtual Human medical student. Half of the subjects interact with an animated virtual human medical student while the other half interacts with a pre-recorded human. The interactions from this assessment are audio-recorded, transcribed, and then graded to see how the two modalities compare. If the performance when using virtual humans for standardized patients is equal to or superior to pre-recorded humans, this can be utilized as a part task trainer that brings standardized patients to a higher level of effectiveness and standardization. In addition, if executed properly, this tool could potentially be used as a part task trainer which could provide savings in training time, resources, budget, and staff to military and civilian healthcare facilities
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