Educational robots prove effective in children’s learning, but designing robots that support parent-child dialogue during home learning remains unclear. This study proposes a semi-autonomous para-operated robot that parents partially control while engaging with their child. We hypothesized that unlike autonomous robots which may reduce parental engagement [1], this approach would increase parental involvement through active operation. We conducted an experiment with parent-child pairs comparing no robot, autonomous robot, and the proposed semi-autonomous robot conditions. Results showed the proposed robot significantly increased parental utterances without increasing parental burden, demonstrating its effectiveness in facilitating parent-child home learning dialogue.

In personality trait analysis, self-evaluation through questionnaire methods is widely used due to ease of implementation and analysis. However, respondents can easily provide false evaluation scores based on their intentions. This study proposes a method to obtain truthful evaluation scores from dialogue records through dialogue simulation with autonomous agents for questionnaire items. Since dialogue requires immediate responses and detailed explanations, we hypothesized this method would be less prone to deception compared to traditional questionnaire methods. We developed a comprehensive system using Large Language Models that handles everything from setting dialogue situations based on questionnaire items to conducting dialogues with autonomous agents, and automatically evaluating dialogue records. In preliminary experiments, we found that evaluation scores from the proposed method when participants were prompted to lie were close to truthful questionnaire responses when participants were prompted to answer truthfully. These findings suggest the effectiveness of psychological measurement through dialogue with autonomous agents.

Agents that migrate across different devices can provide seamless support for users in various contexts. However, little is known about how users determine whether a migrating agent remains the same individual across different devices. To explore the key factors influencing users’ perception of agent continuity before and after migration, we conducted two experiments. In Experiment 1, we examined how users’ perception is influenced when two visually identical agents differ in any of the three factors: voice, memory, or speaking style. Experiment 2 tested whether maintaining the factors identified as critical in Experiment 1 would enable users to perceive the agent as the same individual after it migrated from a robot to headphones. Results suggest that while changes in the factors can disrupt perceived continuity, preserving them enables consistent identity perception before and after migration, even when the agent’s appearance changes.

Co-located operated robots, where an operator, a robot, and a user interact in the same physical space, are an emerging paradigm in human-robot interaction. This para-operation approach aims to reduce operator workload and enhance communication. A key challenge is balancing robot autonomy with operator intent; fully manual systems lack flexibility, while fully autonomous ones risk unintended actions. To address this, we propose a semi-autonomous system that uses an augmented reality (AR) interface for intuitive control. We developed a prototype where an operator’s AR glasses display contextual action choices for the robot. A preliminary user study was conducted in a simulated retail scenario. Results from interviews showed that the desired dialogue strategy depends on the operator’s proficiency. Novices preferred robot-led interaction for guidance, while experienced users favored operator-led support for nuanced control. These findings highlight the need for adaptive dialogue strategies in AR-based para-operation, offering initial insights for this collaborative framework.

An ITACO agent is a conversational agent that migrates across multiple devices to provide user support through the most suitable embodiment while maintaining a continuous relationship with the user. However, because the agent must operate on diverse devices with unique configurations and behaviors, scaling the system significantly increases implementation complexity and development effort. To address this, we propose a platform that serves as a foundational framework to streamline ITACO agent development. Our system simplifies the process of integrating new devices and defining their behaviors, enabling scalable, efficient development of migrating agents. In this paper, we present the design and implementation of this platform and report on a preliminary user study conducted to evaluate its viability. The primary contribution of our work is the core design of a foundational system that facilitates the future development of ITACO agents.

Teleoperated customer service robots have attracted attention to improve customer service efficiency. However, operators experience boredom during long-duration operation due to monotony and idle time, leading to decreased task motivation. This study proposes and evaluates a method to reduce operator boredom through dialogue with the robot to be operated. Field experiments demonstrated that operator-robot dialogue significantly reduced boredom and contributed to maintaining task engagement during long-duration operation.

In recent years, numerous studies have been conducted on dialogue robots powered by large language models,enabling sophisticated interactions such as providing guidance and engaging in small talk. However, the interaction performance remains imperfect, and the robots sometimes cause problems during interactions. In this study, we aim to automatically detect such anomalies in human-robot interactions by creating a dataset and developing anomaly detection models. To this end, we created a dataset by manually annotating videos of in-the-wild interactions collected from our field experiment designed to test a framework of parallel conversations in which a human intervenes when a problem occurs in the interaction. Using this dataset, we trained classification models to construct anomaly detection models. We then conducted another field experiment in which the model’s detection results were presented as alerts to operators within the parallel conversation framework. The results confirmed that providing alerts on the basis of the anomaly detection model was useful for facilitating operator intervention.

Mobile Edge Computing (MEC) is attracting attention as a solution to increasing network traffic load. To build an MEC system, edge servers are placed on base stations and the users must be allocated to edge servers. The conventional MEC method places edge servers and allocate user jobs by using extension of k-means to minimize the number of hops between a user and servers. With this method, however, heterogeneous environments are not assumed, which means the performance difference among edge servers. When many jobs arrive at edge servers with low performance, jobs overflow and transfer to the cloud servers. The initial value dependence of this conventional method has also not discussed. We propose a method for initial edge-server placement and job reallocation in order to apply heterogeneous edge servers and initial value dependence.

Interactive systems that enable people to easily access mental health care in their daily lives are being studied. Self-instruction training, which is a kind of cognitive-behavioral therapy, is expected to be effective for general-purpose mental health care, but the difficulty for users to create self-instructional texts by themselves has hindered its widespread use. Furthermore, it is not sufficient to simply use a computer-assisted method for the training in which the computer automatically generates the self-instructional texts. This is because previous studies have shown that users do not feel self-instructional texts that are not created by themselves are their thoughts, and consequently cannot internalize the content of the texts, reducing the effectiveness of the training. In this study, we focused on the interface design that facilitates users to internalize automatically generated self-instructional texts, toward the realization of a self-instructional training support system. We proposed an interface that shows the real-time captured video of a user's face like a mirror and superimposes a speech bubble containing a self-instructional text to be connected to the user's face and confirmed the interface facilitates the user's internalization of the text through online experiments. The contribution of this paper is to provide a novel interface design for computer-assisted self-instructional training.

This study investigates the effects of both operator and avatar gender on the perceived ease of communication and creepiness of the avatars. Utilizing a mixed-methods 2 by 2 approach (male operator, female operator; male avatar, female avatar), we conducted an experiment involving 148 participants. The results indicate significant variations in perceived avatar impressions influenced by the gender alignment between the operator and the avatar. Specifically, female-operator-female-avatar group rated as the easiest to talk to, most interesting and least in the creepiness metric. These results suggest that for low-friction conversational encounters using female-operator-female-avatars might be most suitable.

Cybernetic avatars (CAs), robots or CG agents operated remotely by humans, are increasingly used for remote communication, offering potential for applications such as telework. However, the usability of these systems, particularly regarding the operator’s sense of agency (SoA) and sense of ownership (SoO), remains underexplored. We conducted an experiment using a commercially employed CA system. The results showed that operators can experience SoA and SoO over on-screen CG avatars, supporting the system’s basic usability. Additionally, the results suggest that limiting operator hand movements might better maintain SoA in environments with a delay in the reflection of operators’ movement on CAs. These findings have preliminary implications for CA system usage, highlighting the need to consider trade-offs between operation and system responsiveness.

Teleoperated social robots have been widely studied and employed, yet their operation interfaces provide limited information to the operator, causing difficulties in grasping the dialogue situation compared to face-to-face interactions. Particularly with conventional interfaces, operators face challenges with vocal adaptation due to the inability to assess the distance between the robot and the interlocutor. Consequently, operators struggle to determine the appropriate volume level for clear communication, leading to insecurity about their vocalization’s effectiveness. In this study, we propose a novel approach to address this issue: a voice volume gauge that enables operators to adjust their voice volume by displaying the difference between their current volume and the estimated optimal volume on the interface. We implemented the gauge and conducted a subjective evaluation experiment, which demonstrated no usability concerns for operators and a reduction in their insecurity levels. Furthermore, preliminary objective evaluation results based on speech analysis suggest that utilizing the gauge may bring operators’ vocalizations closer to those in face-to-face dialogues. The contribution of this paper lies in providing a simple interface design method to aid in solving the vocal adaptation problem for teleoperated robot applications.

Various customer service robots’ teleoperation interfaces (I/Fs) have been developed for human-robot collaboration. However, a previous study has indicated a lack of operator enjoyment. This study aims to design an I/F that elicits operator enjoyment and identifies the factors that contribute to this enjoyment. We developed two I/Fs: a high degree of freedom I/F and a gradual flexibility degree of freedom I/F based on gamification to elicit operator enjoyment. Using these I/Fs, we conducted a field study in a real shopping mall to investigate the operators’ experiences. As a result, the operators in this experiment greatly enjoyed using our I/Fs. The results showed that our I/Fs could elicit operator enjoyment with the following three I/F factors suggested as potentially important design guidelines: ease of use through anonymity, moderate restriction of freedom, and sharing experiences with a group of operators.

Dialogue robots powered by large language models can generate advanced utterances. However, the interaction performance is not yet perfect, and the robots sometimes cause problems during interactions. In this study, to detect anomalies in human-robot interactions, we created a dataset and constructed anomaly detection models. For the dataset creation, we collected videos of human-robot interactions in a framework where humans intervene when a dialogue breakdown occurs and labeled the scenes where humans intervened as anomalies. Using this dataset, we built classification models and deep metric learning models utilizing encoders for video, audio, and multimodal information. The results showed that we could successfully train the models and achieve an accuracy and F1-score of over 80%. The performance of the deep metric learning models surpassed that of the classification models, thus demonstrating the importance of separating the differences between classes. We also clarified the importance of audio information.

While research and applications of operated social robots that can be used as operators’ avatars have been conducted, a para-operated social robot has also been proposed, in which the robot and its operator exist in the same space, and the operator, robot, and interlocutor can interact with each other. From the findings of human-human-robot interaction research, it is known that the robot’s behavior influences the interpersonal relationships of the people involved in the dialog. However, there is no knowledge of how the operator is perceived by the interlocutor when the operations by the operator are unveiled. This paper reports preliminary results from two online surveys conducted to investigate the following question considering the robot-operator distance; Does the impression of the operator improve in unveiled para-operation when the operator operates the robot and has it say favorable utterances? The results of the two video surveys conducted at different distances between the robot and the operator show that the impression of the operator was improved by the robot’s favorable humorous utterances when the distance was close, but not when the distance was further apart. We consider that the findings contribute to the potential application of unveiled para-operated robots and suggest the importance of considering the distance factor in the influence of robots on human-human relationships.

In recent years, a framework of parallel conversations has been proposed to facilitate efficient conversations through cooperation between humans and dialogue systems. This approach aims to enable simultaneous conversations with multiple users by enabling the system to handle basic conversation and human operators to intervene when problems arise in the system’s conversation. Previous studies on parallel conversations have primarily focused on delegating simple exchanges such as greetings and acknowledgments to the system, with humans taking over for more complex interactions like providing guidance. Recent advancements in large language models may change this situation, enabling dialogue systems to engage in more advanced interactions. In this study, to examine which interventions will be made when large language models are utilized, we placed six dialogue robots based on large language models in an actual facility and conducted a field experiment involving parallel conversations for about a month. Our analysis of the collected data on dialogues and interventions showed that the most frequent interventions were made for supporting interactions when the system failed to react to the user utterances, indicating the limitations of using large language models alone and clarifying our next steps for facilitating smoother parallel conversations.

Dialogue systems are widely utilized in chatbots and call centers. However, it is often difficult for such systems to deliver fully autonomous dialogue. For users to have a better dialogue experience, a framework for human-system collaborative dialogue is proposed in which a human operator takes over the dialogue when needed, engaging in conversation with the user instead of the system (we call this process intervention). Operators join the dialogue in the middle; therefore, it is believed that dialogue summarization can be helpful for interventions. However, it is currently unclear whether dialogue summarization is actually useful. Therefore, in this study, we aim to investigate the usefulness of dialogue summaries for interventions through a field experiment conducted at an actual facility combining an aquarium and a zoo. The results of the field experiment revealed that dialogue summaries were more useful for intervention than dialogue history. Furthermore, we found no differences in the word categories included in the operator utterances during interventions irrespective of whether the dialogue history or dialogue format summary was presented to the operators, suggesting that dialogue format summary has content similar to that of dialogue history but improves the usefulness in intervention.

Under the circumstances that social robots are increasingly being developed and studied in service encounters at public spaces, are they introduced into residential environments (i.e., private space)? This study hypothesizes that a personal assistant device in residential environments should wear human-like appearance to engage in service as conversation partner. We implemented the interaction design that provides regular services as the current personal assistant and additional service as conversation partner, and then conducted a field experiment where the participants stayed in the hotel rooms with a smart speaker or a social robot. The results support the hypothesis in that of conversation amount and emotional experience by conversation. The results also suggest the possibility of commercial service, namely conversational advertisement through social robots.

Emotional labor in text-based chat environments will be widespread in the near future. It is difficult for novice workers to make smooth conversation with an angry customer in a customer-support work- ing environment, one of the stressful emotional labors. In this pa- per, we propose a method to suppress the customer's anger based on a communication agent introduced into customer-support work in order to facilitate smooth communication. The agent first estab- lishes a positive relationship with the customer, and then the atti- tude changes to be sympathetic to the customer-support worker in order for the customer to follow sympathy and reduce anger. From the experimental evaluation, it is found that there is the possibil- ity of suppressing the participants' anger by this method, but the anger itself is at a higher level than in the common environment without the agent.

While more and more robots have been employed in the service industry, the impact of the human--robot social interaction on a heartwarming interaction service mostly remains an open question. For the purpose of exploring the possibility that a humanoid robot engages in a heartwarming interaction service, we developed herein the first prototype of the service system through a humanoid robot and conducted a field study, where a humanoid robot engages in the service for a customer at a hotel to collect a customer's impression of the service by questionnaire. The results demonstrate a humanoid robot's potential of engaging in a heartwarming interaction service that enhances customer satisfaction of the whole service. An exploratory analysis suggests the differences of the impact in sex and long-term interaction. Finally, we discuss the possibility of another application, namely, effective advertisement through a heartwarming interaction with a humanoid robot.

Hiroshi Ishiguro gave a lecture to a group of young students. We employed CommU, the desktop social robot, to manage the questions and answers for the talk. We encouraged the students to ask questions anytime. Half of the classroom was told to ask questions by raising their hand while the other half was shown an online messaging system developed for CommU, which allows the audience to post questions, which the robot would directly say. We had a gatekeeper to monitor for invalid sentences. In the middle of the presentation we asked the students to shift roles. The robot used a neural network based estimator of interruptibility to find the best time to speak. We did not expect too many questions, but the audience really embraced using the robot. They posted 44 questions to the presenter through CommU. On the other hand they asked 8 direct questions by raising their hands and standing up. Students thought that they gained more information from the lecturer using the robot than using the conventional method. In this instance we didnt stop the students from asking too many questions, but in a real-world application the gatekeeper will have to play an important role.

In recent decades and years classroom teaching has been influenced by the appearance of digital devices and the pervasiveness of the internet. In recent years robots started appearing in learning environments. Even though classroom presentations improved considerably, interaction between students and teachers has not improved greatly. We propose a new way of using a desktop robot and an online voting/messaging system to make the classroom experience more interactive. Concretely, in this paper we report on a lecture which was assisted by a robot. The students posted questions and opinions on an online messaging platform. The messages were then sent to the robot to be posed to the teacher, either directly or through a voting procedure. Students found this new way of interaction very efficient and useful for improving their communication with the teacher. At the same time the number of interactions should be controlled so it does not interfere with the teaching process.

Being ubiquitously used as anti-adhesive and wound-covering mechanisms, thin films have potential therapeutic uses as cell sheets to target inner organs while navigating narrow environments. A significant challenge to realize versatile films lies in achieving compact storage and efficient transport while ensuring coherency in curvature-bounded environments. In this paper, we propose a folding mechanism of a curved film by using a spiral approach, enabling efficient unfolding and flexible plasters with curved surfaces. Our experiments using gelatin-based films with curved surfaces shows the superior indwelling ability in terms of chromaticity level compared to the conventional planar films, as well as the efficient unfolding in the order of seconds. Our results presents the theoretical and experimental building blocks to realize a versatile class of films which are able to navigate narrow environments, and unfold efficiently and flexibly.

The behavior of a social robot is designed based on either its emotional state or social situation. In this research, we defined these expressions as the affective and social expressions, and proposed a new emotional expression method to integrate these two expressions. It is known that a human has involuntary facial muscles around the eyes, and voluntary facial muscles around the mouth. Thus, it is considered that facial muscles around the eyes express the affective expressions, while facial muscles around the mouth express the social expressions. In an experiment involving a human-robot conversation, using the proposed method, the results showed a sense of human likeness and sociality. Furthermore, the intimacy evaluation results showed that the social expressions work effectively when the intimacy does not require high social bonding such as the desire for friendship. However, the affective expressions are necessary for evaluating intimacy that requires higher social bonding, such as wanting to live with someone.

The future role of android robots is discussed. Survey results reveal that people are capable of viewing androids as companions and will accept androids operating in various roles within human society; however, people are uncomfortable with androids operating in roles in which they are able to persuade humans to do something, affect humans' minds, or supervise young children. To examine people's response to an actual android robot within human society, an android capable of operating as "lecturer" was implemented and an evaluative experiment conducted. It was found that androids can evoke feelings of attentiveness that are much stronger than those evoked by existing media. Furthermore, use of the lecturer android did not improve efficiency. It is possible that people expected the android to have human-like abilities because of its human-like appearance. However, regardless of the cause, it is clear from the experiment that it is necessary to program androids with more human-like functions if they are to fill useful roles within human society.

In this paper, we discussed an autonomous android robot that is recognized as a social entity by observers in the real world. We conducted field experiments to investigate what kind of function the android needs in order to be recognized as a social and humanlike entity by visitors. In the field experiment, the android made conversation with multiple visitors by using several touch displays. The result showed that the visitors evaluate the android as humanlike even though this interaction differs from normal human-human interaction. Moreover, the experiment suggested that the android has a social influence - advertisement effect on visitors.

In recent applications with massive but less reliable data (e.g., labels obtained by a semi-supervised learning method or crowdsourcing), non-robustness of the support vector machine (SVM) often causes considerable performance deterioration. Although improving the robustness of SVM has been investigated for long time, robust SVM (RSVM) learning still poses two major challenges: obtaining a good (local) solution from a non-convex optimization problem and optimally controlling the robustness-efficiency trade-off. In this paper, we address these two issues simultaneously in an integrated way by introducing a novel homotopy approach to RSVM learning. Based on theoretical investigation of the geometry of RSVM solutions, we show that a path of local RSVM solutions can be computed efficiently when the influence of outliers is gradually suppressed as simulated annealing. We experimentally demonstrate that our algorithm tends to produce better local solutions than the alternative approach based on the concave-convex procedure, with the ability of stable and efficient model selection for controlling the influence of outliers.

Due to human sensitivity for humanlike objects, designing human-like behavior for a robot that interacts with humans remains a central issue in the HRI field. This issue is formidable because human-likeness is an important factor for better interaction since it can easily convey negative impressions if the design is not perfect, as in the uncanny valley phenomena. This paper addresses this issue with a novel approach that utilizes implicit know-how for performing on stage and is dedicated to represent human beings. Contemporary colloquial theatre theory (CCTT), which is a method of directing plays, is appropriate for this purpose since its reality-oriented instructions are directly applicable for improving robot behavior. In this paper, we report case studies on performing a play involving both humans and a robot. The play in our study was evaluated in public performances in Japan. We report detailed analysis of comparable short plays on human-robot interaction or human-human-robot interaction. Our analysis implies that utterance and motion timings should be tuned depending on the situation. Future work will use a motion capture system to get more precise data and more useful knowledge.

In this paper, time evolutions of students’ knowledge level who are engaged in collaborative learning, is simulated using mathematical model. In this model, students try to acquire hierarchic-structured knowledge. It is found that the structure of the collaborative groups formed by the students influence their achievements. Collaborative learning is said to be useful because one can reach the level where one cannot reach with the traditional teaching approach. We have the result that collaborative learning is especially effective when learning the difficult knowledge and we might be able to say our model successfully described the aspect of collaborative learning.

The semi-supervised support vector machine (S3VM) is a maximum-margin classification algorithm based on both labeled and unlabeled data. Training S3VM involves either a combinatorial or non-convex optimization problem and thus finding the global optimal solution is intractable in practice. It has been demonstrated that a key to successfully find a good (local) solution of S3VM is to gradually increase the effect of unlabeled data, a la annealing. However, existing algorithms suffer from the trade-off between the resolution of annealing steps and the computation cost. In this paper, we go beyond this trade-off by proposing a novel training algorithm that efficiently performs annealing with an infinitesimal resolution. Through experiments, we demonstrate that the proposed infinitesimal annealing algorithm tends to produce better solutions with less computation time than existing approaches.

In this paper, we claim that some of the non-support vectors (non-SVs) that have no influence on the classifier can be screened out prior to the training phase in pathwise SVM computation scenario, in which one is asked to train a sequence (or path) of SVM classifiers for different regularization parameters. Based on a recently proposed framework so-called safe screening rule, we derive a rule for screening out non-SVs in advance, and discuss how we can exploit the advantage of the rule in pathwise SVM computation scenario. Experiments indicate that our approach often substantially reduce the total pathwise computation cost.

As a promising wireless access standard for machine-to-machine (M2M) networks, the IEEE 802.11 task group ah has been discussing a new standard which is based on the wireless local area network (WLAN) standard. This new standard will support an enormous number of stations (STAs) such as 6000 STAs. To mitigate degradation of the throughput and delay performance in WLANs that employ a carrier sense multiple access with collision avoidance (CSMA/CA) protocol, this paper proposes a virtual grouping method which exploits the random arbitration interframe space number scheme. This method complies with the CSMA/CA protocol, which employs distributed medium access control. Moreover, power saving is another important issue for M2M networks, where most STAs are operated by primary or secondary batteries. This paper proposes a new power saving method for the IEEE 802.11ah based M2M network employing the proposed virtual grouping method. With the proposed virtual grouping and power saving methods, the STAs can save their power by as much as 90% and maintain good throughput and delay performance.

In this study, we examine the factors with which robots are recognized as social beings. Participants joined sessions of the Ultimatum Game, a procedure commonly used for examining attitudes toward others in the fields of economics and social psychology. Several agents differing in their appearances are tested with speech stimuli that are expected to induce a mentalizing effect toward the agents. As a result, we found that while appearance itself did not show significant difference in the attitudes, the mentalizing stimuli affected the attitudes in different ways depending on robots' appearances. This results showed that such elements as simple conversation with the agents and their appearance are important factors so that robots are treated more humanlike and as social beings.

In recent years, research has increased on very human-like androids, generally investigating the following: (1) how people treat such very human-like androids and (2) whether it is possible to replace such existing communication media as telephones or TV conference systems with androids as a communication medium. We found that androids have advantages over humans in specific contexts. For example, in a collaboration theatrical project between artists and androids, audiences were impressed by the androids that read poetry. We, therefore, experimentally compared androids and humans in a poetry-reciting context by conducting an experiment to illustrate the influence of an android who recited poetry. Participants listened to poetry that was read by three poetry-reciting agents: the android, the human model on which the android was based, and a box. The experiment results showed that the enjoyment of the poetry gained the highest score under the android condition, indicating that the android has an advantage for communicating the meaning of poetry.

We previously investigated body ownership transfer to a teleoperated android body caused by motion synchronization between the robot and its operator. Although visual feedback is the only information provided from the robot, due to body ownership transfer, some operators feel as if they were touched when the robot's body was touched. This illusion can help operators transfer their presence to the robotic body during teleoperation. By enhancing this phenomenon, we can improve our communication interface and the quality of the interaction between operator and interlocutor. In this paper, we examined how the change in the operator's perspective affects the body ownership transfer during teleoperation. Based on past studies on the rubber hand illusion, we hypothesized that the perspective change will suppress the body owner transfer. Our results, however, showed that in any perspective condition, the participants felt the body ownership transfer. This shows that its generation process may differ in the body ownership transfer for teleoperated androids and the rubber hand illusion.

Teleoperated androids, which are robots with humanlike appearances, are being produced as new media of human relationships. We explored the potential of humanoid robots and how they affect people in the real world when they are employed to express a telecommunication presence and a sense of ‘being there’. We introduced Telenoid, a teleoperated android, to a residential care facility to see how the elderly with dementia respond to it. Our exploratory study focused on the social aspects that might facilitate communication between the elderly and Telenoid's operator. Telenoid elicited positive images and interactive reactions from the elderly with mild dementia, even from those with severe cognitive impairment. They showed strong attachment to its child-like huggable design and became willing to converse with it. Our result suggests that an affectionate bond may be formed between the elderly and the android to provide the operator with easy communication to elicit responses from senior citizens.

The first robotic copies of real humans have become available. They enable their users to be physically present in multiple locations at the same time. This study investigates what influence the embodiment of an agent has on its persuasiveness and its perceived personality. Is a robotic copy as persuasive as its human counterpart? Does it have the same personality? We performed an experiment in which the embodiment of the agent was the independent variable and the persuasiveness and perceived personality were the dependent measurement. The persuasive agent advertised a Bluetooth headset. The results show that an android is found to be as persuasive as a real human or a video recording of a real human. The personality of the participant had a considerable influence on the measurements. Participants that were more open to new experiences rated the persuasive agent lower on agreeableness and extroversion. They were also more willing to spend money on the advertised product.

In this paper we describe an ITACO system that is able to construct an emotional relationship between humans and interactive systems by a migratable agent. The agent in the ITACO system can migrate between interactive systems within an environment. We conducted psychological experiments to verify whether the ITACO system can construct an emotional relationship between humans and interactive systems such as a robot and a table lamp. The experimental results show that emotional relationships were constructed between humans and interactive systems. Thus emotional relationships gave an influence to human’s behavior and cognitive abilities.

We propose a concept of Ubiquitous Cognition and introduce an integrated agent for communication (ITACO) system based on the concept. To realize our proposed concept, the ITACO system tries to appropriately support a user using a migratable agent which is context-sensitive and gives continuous assistance. The key factor in this system is the construction of a relationship between the user and the agent, and to carry on this relationship between the user and the object that the agent has migrated to. Psychological experiments were carried out to verify this succession of the relationship between media. The results of the experiments showed that the subjects' attachment to the media as well as the relationship was succeeded through the media by the agent migration.