This paper presents an overview of Talking-Bones where the robot aims to communicate with humans in a conversation recalling together. Talking-Bones exhibits encouraging behaviors by forgetting some words in a story and asking humans to help to recall the words together in order to continue telling the story. In our field work, we observed that people found the forgotten words together and enjoyed teaching the robot often laughing and smiling. From this exercise in Joint-Remembering, we suggest that Talking-Bones has the ability to bring out helping behaviours and facilitate communication. In this paper we describe the concept of Talking-Bones and details of the robot design. Also, we describe part of the observed interaction.

The general principle about human-robot conversation is that the conversation of a robot should emphasize on providing complete information in a single utterance, without the necessity of a human asking further questions. On the other hand, information deficiency is found commonly in human-human conversation. In particular, between a child and a caregiver; even though the child has a limited speaking ability, they can build a deep bond by means of the positive and interactive support of their caregiver. Unlike many kinds of research whose aim is to make a robot possess a superior ability to have a natural conversation with a human, in this research, we focus on the incompleteness in a robots' conversation by utilizing some strategies such as information deficiency and ellipsis. Herein, it is important to understand the behaviors and responses of the human partner in such a human-robot conversation. This study aims to analyze human responses when a robot speaks to a human with insufficient words. Accordingly, we constructed a syntactic method to create a deficiency in the elements of uttered sentences to analyze the behaviors and replies of a human in a human-robot conversation. The results showed that when the robot used "Semantically Incomplete Utterance"; which means the robot has unclear references in its utterance, the human partner increased the number of questions to the robot, talked further about the new information related to the topics and decreased the number of slight responses. Consequently, the incompleteness in the utterance of a robot attracted cooperative human responses, and the participants increased participation in the domain of conversation.

Robots are expected to become present in society in increasing numbers, yet few studies in human-robot interaction (HRI) go beyond one-to-one interaction to examine how characteristics of robot groups will affect HRI. In particular, people may show more negative or aggressive behavior toward entitative (i.e., cohesive) robot groups, like they do toward entitative human groups, compared to diverse groups. Furthermore, because people in collectivist (e.g., Japan) and individualistic (e.g., US) cultures respond to groups and to cues of entitativity differently, entitative robot groups may affect people differently across such cultures. This study examines how robot Entitativity Condition (Single Robots, Diverse Group, Entitative Group) and Country (USA, Japan) affect emotions toward, mind attributions to, and willingness to interact with robots. Results indicate that Entitative robot groups, compared to Single robots, were viewed more negatively. Entitative robots were also more threatening than Diverse robots. Diverse robot groups, compared to Single robots, were viewed as having more mind, and participants were more willing to interact with them. These findings were similar in the USA and Japan. This indicates that robot group entitativity and diversity is critical to keep in mind when designing robots.